Provisional University Bulletin (2024-2025)

In 1992, the Rabb School of Continuing Studies was named in honor of Norman S. and Eleanor E. Rabb in recognition of more than four decades of support for Brandeis.

With four divisions — Graduate Professional Studies, the Summer School, the Osher Lifelong Learning Institute at Brandeis, and Brandeis Precollege Programs — the Rabb School seeks to serve lifelong learners by supporting the university in its mission of providing open inquiry and outstanding teaching in a world of challenging social and technological transformation.

In 1997, the Division of Continuing Studies, now the Division of Graduate Professional Studies, was established in the Rabb School specifically to extend the opportunity for excellent, applied professional education at the graduate level to a more diverse, part-time, working-adult population. All degree programs in the division are professionally oriented, applied in nature (combining requisite theory with the practical application of learned material), and taught by expert adjunct faculty who are practitioners of their subject matter in their professional lives.

Programs in applied, professional fields are offered in the Division of Graduate Professional Studies of the Rabb School and are overseen by the Rabb School Council.

New programs, as well as substantive changes to the curriculum, are reviewed for approval by the Rabb School Council and as necessary by both the Council of the Graduate Professional Schools and the Academic Affairs Committee of the Board of Trustees.

Currently, the Division of Graduate Professional Studies in the Rabb School offers master's degree programs requiring 10 three-credit courses, and graduate certificates requiring four 3-credit courses, in applied fields:

• Master of Software Engineering (est. 1997)
• Master of Science in Bioinformatics (est. 2002)
• Master of Science in Project and Program Management (est. 2003)
• Master of Science in Digital Marketing and Design (est. 2015)
• Master of Science in User-Centered Design (est. 2015)
• Graduate Certificate in Healthcare Analytics (est 2022)
• Graduate Certificate in Genomics (est. 2023)

• Graduate Certificate in Cheminformatics (est. 2023)

• Graduate Certificate in Drug Discovery (est. 2023)

GPS offers an opportunity for students to earn two master's degrees, sequentially, transferring up to two courses, if appropriate, from the first master's program to the second. If a graduate certificate and master's degree are sought sequentially (as opposed to two master's degrees), the student may transfer up to one course from the first program to the second.

Given the Rabb School’s commitment to making graduate, credit-bearing and professionally oriented academic resources at Brandeis available to as many qualified part-time students as possible, the division offers all programs completely online.

In addition, GPS collaborates with corporate partners in offering credit-bearing courses to special student groups at corporate sites or welcoming corporate-sponsored students in its courses. There are no programs offered through sites other than the Brandeis campus.

How to Apply

Admission policies and procedures for graduate programs in the Division of Graduate Professional Studies are described in detail in both the GPS website and the Student Handbook located in the Academic Resources section of the website. Standards of admission to all programs are clear, consistent and simple. Applicants to master’s degree programs in the Rabb School generally hold bachelor’s degrees from regionally accredited U.S. institutions or equivalent.

All formal applications for admission are evaluated by a faculty/staff committee. Applications and admission decisions are made on a rolling basis, with entry points at the beginning of each of the four standard 10-week sessions (July, October, January and April).

Academic Standing

Prior to filing a formal application, students may take up to two graduate courses, thereby determining whether a commitment to both the chosen field and program is appropriate for them. It is standing policy that a course graded below B – may not be applied toward a degree, regardless of when it is taken. Students are allowed a maximum of 12 courses to complete a 10-course master's degree, and a maximum of 7 courses to complete a 4-course graduate certificate.

Students may take up to four years to complete a 10-course program (Most students complete their master's degrees in less than three). Students may take up to three years to complete a 4-course graduate certificate.

Students enrolling in 9 or more credits in a semester are considered to be full-time, per the University guidelines. GPS students may additionally opt in to a “full-time” one-year track for the duration of their program if admitted to the full-time format of the User-Centered Design, Digital Marketing and Design, or Project and Program Management degree program. The GPS full-time track requires students to enroll in five courses per term, for a total of two terms.

Requirements for the Degrees

Detailed information about the requirements for the programs offered by the Division of Graduate Professional Studies, can be found in a later section of this Bulletin or on the GPS website. Please refer to these pages for the requirements and expected learning outcomes for specific degrees.

Auditing Courses

All regularly enrolled, full-time graduate students at Brandeis are eligible to audit by the Division of Graduate Professional Studies courses without a fee. Part-time degree students and non-degree special students may audit a Graduate Professional Studies course but will be charged the same rate as a course taken for credit. No courses may be audited without the permission of the instructor and the student's program chair. Auditors may not take examinations or expect evaluation from the instructor. No credit is given for an audited course. Graduate Professional Studies students are eligible to audit courses of IBS, GSAS and Heller, abiding by their policies.

Attendance

All students are expected to participate in classes regularly. In addition, an individual faculty member may establish attendance requirements for all students in the course, and may insist on the completion of all assignments even if a student was not active in the course for the period.

In rare circumstances, a student may have to miss more than a week of class due to serious illness or to family emergencies. In these cases, a student should be in immediate contact with their student advisor to discuss what options may be available. Because class participation and peer learning are important aspects of the Brandeis educational experience, students who miss more than two weeks of class will need to consult with their student advisor and instructor to discuss a plan for going forward.

Course Drops

A student may drop a course through the sixth week of the session. The refund policy is noted in the Student Handbook located in the Academic Resources section of the GPS website

A student may drop the same required course no more than twice, and a student may drop no more than six courses during the course of completing their program requirements. After the fourth drop, the student will be placed on academic warning.

Incompletes

Incompletes are granted in exceptional cases, arranged between the student and the instructor and documented, including specific closure date, in the division’s office. Unaddressed incompletes become failures after the established deadline. (Refer to the full incomplete policy noted in the Student Handbook.)

Transfer of Credit

Rabb School degree candidates are not permitted to cross-register either in other graduate programs on campus or in programs elsewhere. Up to two courses not previously counted for any degree program may be considered for transfer into a Rabb School degree. This assessment is made as part of the admissions process.

Course Waivers

Students accepted to a master’s degree may occasionally waive out of a required course in which they can demonstrate proficiency. Graduate Professional Studies makes final decisions on course waiver applications. Students do not receive academic credit for waived courses, but instead will be allowed to substitute an elective course in the program, to accrue the necessary amount of credits to graduate. A maximum of two course waivers will be permitted, with approval from the program chair.

International Students

All courses require students to be proficient in English. Students who did not earn a bachelor’s or master’s degree from a regionally accredited United States institution must either submit TOEFL or IELTS scores no more than two years old during the application process or meet one of the following criteria:  

• Will complete or have completed a bachelor’s degree with at least three full-time academic years of study (ESL and online coursework not included) in one of the designated countries below
• Have completed at least a full-time academic year of graduate study in a designated country (online coursework not included) at the time the application is submitted
• Have worked full-time for at least three years in a designated country

Designated countries include: Anguilla, Antigua and Barbuda, Australia, The Bahamas, Barbados, Belize, Bermuda, the British Virgin Islands, Canada, the Cayman Islands, Denmark, Dominica, The Gambia, Ghana, Grenada, Guyana, Iceland, Ireland, Jamaica, Lesotho, Liberia, Malta, Montserrat, New Zealand, Norway, Philippines, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, South Africa, Sweden, Trinidad and Tobago, Turks and Caicos Islands, United Kingdom, or Zimbabwe.

Rabb School Academic Calendar

Fall 224

 

Fall-1 Registration: Wednesday, April 24- Friday, June 28

Fall-1 First Day of Instruction: Wednesday, July 10

Fall-1 Last Day of Instruction: Tuesday, September 17

Fall-2 Registration: Wednesday, April 24 - Tuesday, October 1

Fall-2 First Day of Instruction: Wednesday, October 9

Fall-2 Last Day of Instruction: Tuesday, December 17

Spring 2025

 

Spring-1 Registration: Wednesday, October 30 - Tuesday, December 31

Spring-1 First Day of Instruction: Wednesday, January 8

Spring-1 Last Day of Instruction: Tuesday, March 18

Spring-2 Registration: Wednesday, October 2- Tuesday, March 25

Spring-2 First Day of Instruction: Wednesday, April 2

Spring-2 Last Day of Instruction: Tuesday, June 10

The following tuition and fees are in effect for the 2024-2025 academic year. These figures are subject to annual revision by the Brandeis University Board of Trustees.

Payment of tuition occurs per course registration and must be completed in full in order for the registration to be official and for students to attend the first online course module. Except under rare, prearranged circumstances, students not paid in full are not permitted to enter courses.

• Tuition per three-credit course: $3,660

• Course materials fee (dependent on course needs): $25-250

• Other educational costs for a two-module session include off-campus housing and food ($11,430) and books and supplies ($1,016). 

Refunds

Financial Aid

The Division of Graduate Professional Studies offers no scholarships, grants, or assistantships.

Federal Loans

Only the Federal Direct Unsubsidized Stafford Loan is available to Graduate Professional Studies students. Applicants must file the Free Application for Federal Student Aid to qualify for this loan. Graduate students may borrow up to a maximum of $20,500 a year, not to exceed the cost of attendance, with an aggregate maximum of $138,500, with no more than $65,500 in subsidized loan funds. For the academic year 24-25, the interest rate on the Stafford Loan will be a fixed rate of 8.08 percent and the origination fee will be 1.057 percent.

Repayment of a Stafford Loan begins six months after the borrower ceases to be enrolled at least half-time. The standard repayment period is 10 years, during which time interest is charged. (Please go to https://studentaid.gov/ for information about alternate repayment plans.) Students are required to pay the interest during the in-school period, or have it capitalized and added to the loan balance, for the unsubsidized loan.

 The Graduate PLUS Loan is a federal loan that allows graduate students to borrow up to their total cost of education less any financial aid received. The student must pass an independent credit review. For the 24-25 academic year, the PLUS Loan will be a fixed interest rate of 9.08 percent and an origination fee of 4.228 percent. Go to https://studentaid.gov/ to apply for this loan.

Borrowers of the Federal Direct Stafford Loan, and the Federal Direct Graduate PLUS Loan must complete the required promissory notes and entrance counseling online at the beginning of their entering semester upon receipt of correspondence from the Office of Student Financial Services. Anticipated credits on a student's account will be cancelled if all required steps are not completed.

The terms for the above loan programs are subject to federal legislation, regulations and other guidance, and may change. Students wishing to apply for loans should contact the Office of Student Financial Services for application materials.

Additional Satisfactory Academic Progress Requirement for Students Receiving Financial Aid

Federal regulations require that a student receiving federal assistance make satisfactory academic progress in accordance with standards set by the university. The Division of Graduate Professional Studies is responsible for monitoring academic progress within its graduate programs. To receive federal funding, a student must successfully complete two courses (B- or higher) in each semester in which he or she receives federal loans. If he or she fails to successfully complete two courses in a semester in which he or she receives federal loans, he or she will be allowed to receive federal loans for the next semester but will be placed on probation. If he or she fails to successfully complete two courses during the probationary semester, he or she will lose eligibility for federal loans from this point forward. A student may submit an appeal if there are extenuating circumstances that prevented him or her from successfully completing coursework for two subsequent semesters.

Students enrolled in a graduate certificate are not eligible to receive federal loans.

Financial Regulations

Failure to discharge financial obligations includes, but is not limited to, an overdue balance with the university or the delinquency of a borrower in repaying a loan administered by the Office of Student Financial Services and the inability of that office to collect such a loan because the borrower has discharged the indebtedness through bankruptcy proceedings.

A student who defaults in the payment of indebtedness to the university shall be subject to suspension, dismissal and refusal of a transfer of credits or issuance of an official transcript. Brandeis University may refer delinquent accounts to a collection agency. Students are responsible for paying the collection agency fee, which may be based on a percentage at a maximum of 40 percent of any delinquent account, together with all costs and expenses, including reasonable attorney’s fees, necessary for the collection of any delinquent account. Delinquent accounts may be reported to one or more of the national credit bureaus.

Every student is required to complete a Financial Responsibility Agreement at least once each academic year. Any student who fails to complete this agreement prior to the start of classes will be denied the privileges of attending classes and using university facilities.

Degree of Master of Software Engineering

The Master of Software Engineering prepares students to participate fully in integrated teams of software developers, software acquirers and software end users.

Students have the necessary software engineering skills and knowledge to ensure the delivery of reliable software to increasingly large, complex and international end-user markets.

Program of Study

The Master of Software Engineering consists of 10 courses, 30 credits. There are 6 required courses, and 4 elective courses.

Required Courses

• RSEG 105 – Expert Software Development in Java
• RSEG 109 – Object-Oriented Design with UML
• RSEG 120 – Software Development Methodologies
• RSEG 126 – Release Control and Continuous Integration/Continuous Delivery (DevOps)
• RSEG 127 – Software Engineering Studio
• RSEG 131 – Software Testing Techniques

Electives (choose four)

• RSEG 102 – Software Development in Java
• RSEG 103 – Software Development in C++
• RSEG 128 – User Interface Design
• RSEG 155 – Functional Programming with Java and Scala
• RSEG 161 – Web Development Technologies
• RSEG 165 – Design Patterns
• RSEG 167 – Microservices Architecture and Development
• RSEG 170 – Database Management
• RSEG 176 – Cloud Computing
• RSEG 181 – Agile Software Development
• RSEG 290 – Special Topics in Software Engineering

Cybersecurity Concentration (choose four)

• RIAS 102 – Foundations of Cybersecurity for Software Engineering Professionals
• RIAS 110 – Identity Management and Access Control
• RIAS 120 – Secure Development Technologies
• RIAS 140 – Cloud Security
• RIAS 172 – Network Security

Program Outcomes

Upon completion of this program, students will be able to:

• Apply a systematic, disciplined, quantifiable approach to the cost-effective and secure development, operation, and maintenance of software systems to the satisfaction of their beneficiaries, while adopting software engineering best practices.
• Build solutions using different technologies, architectures and life-cycle approaches in the context of different organizational structures, with demonstrated programming expertise.
• Demonstrate a cross-section of skills necessary to collaborate throughout the phases of software development including requirements, design, implementation, testing, and release management.
• Apply foundational software engineering skills to support specialization in focused disciplines such as web & mobile development, design, cloud computing, and databases.
• Communicate effectively and think critically about a wide range of issues arising in the context of working constructively on software projects.

Degree of Master of Science in Project and Program Management

The Master of Science in Project and Program Management provides current and potential project managers with an integrated understanding of a broad scope of business functions at the upper-middle, team-leading level of corporate operations, combined with the technical skills and knowledge to analyze, organize and manage the expression of projects, on time and on budget.

Program of Study

The degree of Master of Science in Project and Program Management requires seven required courses and three electives, totaling 10 courses (30 credits).

​Required Courses

• RPJM 101 - Foundations of Project Management
• RPJM 103 - Project Scheduling and Cost Management
• RPJM 110 - Risk Management in Projects and Programs
• RPJM 113 - Negotiating and Conflict Resolution
• RPJM 117 - Program Management: Theory and Practice
• RPJM 119 - The Human Side of Project Leadership
• RPJM 130 - Demystifying Agile Project Management

Electives (choose three)

• RCOM 202 - Communication for Effective Leadership
• RPJM 115 - Challenges in Project Management
• RPJM 118 - Procurement and Contract Management
• RPJM 135 - Agile Tools and Techniques 
• RPJM 290 - Special Topics in Project and Program Management
• RSAN 101 - Foundations of Data Science and Analytics
• RSAN 190 - Agile Project Management for Analytics

Program Outcomes

Upon completion of this program, students will be able to:

• Lead successful projects and manage the project lifecycle in all its phases in a way that assures the delivery of the negotiated scope and quality level, while meeting time and budget constraints.
• Effectively communicate the project/program status, issues, expectations and risks, both verbally and in writing, to project and program stakeholders and team members.
• Demonstrate and communicate how projects contribute to an organization’s ability to realize its strategic goals and business benefits.
• Exercise leadership, management, and facilitation skills in the conduct of programs and projects of various size, scope and complexity that may be global in nature.
• Effectively manage the roles, communications and expectations of project stakeholders throughout the lifecycle of the project.

Degree of Master of Science in Bioinformatics

The Master of Science in Bioinformatics brings together disciplines including biology, computer science, statistical data modeling and information technology.

Students must develop an understanding of and be able to contribute directly to the analysis of biological data, the design of databases for storage, retrieval and representation of biomolecular data and the development of novel computational tools.

Students’ work will support better understandings of biological systems, human disease and drug development, ultimately affecting the practice of modern medicine.

Program of Study

The degree of Master of Science in Bioinformatics requires six required courses and four electives, totaling 10 courses (30 credits).

Required Courses

• RBIF 100 - Bioinformatics Scripting and Databases with Python
• RBIF 102 - Molecular Biology, Genetics, and Disease
• RBIF 109 - Biological Sequence Analysis
• RBIF 111 - Biomedical Statistics with R
• RBIF 112 - Mathematical Modeling for Bioinformatics
• RBIF 114 - Molecular Profiling and Biomarker Discovery

Electives (choose four)

• RBIF 101 - Structural Bioinformatics
• RBIF 106 - Drug Discovery and Development
• RBIF 108 - Computational Systems Biology
• RBIF 110 - Cheminformatics
• RBIF 115 - Statistical Genetics
• RBIF 120 - Research Topics in Computational Biology
• RBIF 290 - Special Topics in Bioinformatics

Program Outcomes

Upon completion of this program, students will be able to:

• Process and clean, store, analyze and model large volumes of biological data from multiple sources.
• Independently and collaboratively provide insights into complex biological systems through data synthesis, experimental design, and application of a wide range of computational biology approaches.
• Effectively communicate and present bioinformatics concepts to multidisciplinary project teams.

Degree of Master of Science in Strategic Analytics

Strategic Analytics are critical to the strategic management of any business or organization. The management, analysis, and use of the large sets of data that form the foundation of any business operation are what drive the strategic decisions that increase revenue and reduce costs for the organization.

The Strategic Analytics program offers a comprehensive study of these two components: the data itself and its business application, analyzed through a specific set of tools and techniques. Through the study of predictive, descriptive and prescriptive analytics, students will learn to identify patterns and trends within data to interpret and communicate the results in valuable and practical terms.

Program of Study

The degree of Master of Science in Strategic Analytics requires that students complete seven required courses and three electives, totaling 10 courses (30 credits).

​Required Courses

• RSAN 101 – Foundations of Data Science and Analytics
• RSAN 110 – Strategic IT Leadership: Powering Digital Transformation for Enhanced Global Performance, Growth, and Sustainability through Business Intelligence and Analytics
• RSAN 120 – Statistics and Data Analysis
• RSAN 130 – Data Visualization for Strategic Analytics
• RSAN 150 – Data Governance
• RSAN 160 – Predictive Analytics and Machine Learning
• RSAN 175 – Analytics Strategy and Management

Electives (choose three)

• RCOM 202 – Communication for Effective Leadership
• RSAN 140 – Marketing and Customer Analytics
• RSAN 177 – Data Security, Privacy and Ethics
• RSAN 190 – Agile Project Management for Analytics
• RSAN 290 – Special Topics in Strategic Analytics
• RSEG 170 – Database Management
• RSEG 176 – Cloud Computing

Program Outcomes

Upon completion of this program, students will be able to:

• Apply analytics and data to drive strategic objectives, support competitiveness, and enable operational efficiencies.
• Identify and assess the opportunities, needs and constraints for data governance, data management, and reporting within a strategic organizational context.
• Effectively communicate the role and value of analytics in supporting organizations’ strategic goals and operational objectives.
• Develop persuasive narratives through data visualization and business intelligence best practices in order to build consensus and to effectively communicate analysis results.
• Apply current project and change management methodology in delivering successful analytics projects.
• Competently use analytic tools, environments, and modeling techniques to effectively work with diverse datasets.
• Detail legal considerations, ethical considerations, data ownership and privacy considerations inherent in the collection and use of data.

Degree of Master of Science in Digital Marketing and Design

The marketing industry has changed. Businesses once relied primarily on paid media attention, and to some extent on earned media attention. With the advent of digital marketing, businesses are coming to rely on a converged media marketing model, which includes owned media attention (leveraging a channel created and controlled by the business, e.g. blogs, twitter feed, etc). The success of an individual business depends on the ability of the digital marketing specialists to understand and exploit these new models.

The Master of Science in Digital Marketing and Design program blends principles of design, tactics, and analysis across digital marketing, with a practical and applied focus. This program will cover the design and development of interactive media for use in digital marketing, the tactics necessary to deploy digital marketing initiatives, and the analytical frameworks to assess what is working and what is not in order to grow and optimize digital marketing campaigns. Students will gain a solid foundation in current web, media, and interface design practices across multiple platforms. Armed with the skills that inform what is technically, possible, students will then explore techniques to envision, plan, manage, and analyze digital marketing campaigns. Candidates will exit the program with a rich toolkit suitable for bringing a sound digital marketing approach to a variety of industries and companies.

Program of Study

The degree of Master of Science in Digital Marketing and Design requires that students complete seven required courses and three electives, totaling 10 courses (30 credits).

Required Courses

• RDMD 102 – Digital Marketing Strategy
• RDMD 110 – Search Engine Marketing and Optimization
• RDMD 120 – Writing for Digital Environments
• RDMD 130 – Multichannel Marketing Campaigns
• RDMD 135 – Conversion Rate Optimization
• RSAN 140 – Marketing and Customer Analytics
• RUCD 101 – User Experience Design

Electives (choose three)

• RCOM 202 – Communication for Effective Leadership
• RDMD 150 – Multimedia Creation for Campaign Storytelling
• RDMD 160 – Ethics in Digital Design and Marketing
• RDMD 290 – Special Topics in Digital Marketing and Design
• RPJM 101 – Foundations of Project Management
• RSAN 110 – Strategic IT Leadership: Powering Digital Transformation for Enhanced Global Performance, Growth, and Sustainability through Business Intelligence and Analytics
• RSAN 130 – Data Visualization for Strategic Analytics
• RSEG 128 – User Interface Design
• RUCD 130 – Information Architecture
• RUCD 140 – Research Methods
• RUCD 150 – Design Ideation and Prototyping
• RUCD 175 – Inclusive Design & Digital Accessibility

Program Outcomes

Upon completion of this program, students will be able to:

• Develop and actively manage digital marketing campaigns across social media, website and mobile platforms
• Build, design, manage, drive and direct effective content for digital audiences.
• Apply analytic tools and data-driven methods to evaluate digital marketing initiatives and make tactical decisions.
• Optimize the customer journey and ensure alignment with organizational goals
• Create and communicate a digital marketing strategy that supports broader strategy and growth objectives.

Degree of Master of Science in User-Centered Design

The Master of Science in User-Centered Design program prepares students to guide a human-centered perspective in such areas as User Interface Design, Human Computer Interaction, Human Factors, User Experience (UX) and related specializations. The program provides students with the opportunity to develop a portfolio of artifacts that demonstrate their knowledge and ability to apply innovative thinking and a human centered approach to design as well as the leadership skills needed to implement and advocate for design thinking to foster innovation.

Program of Study

The degree of Master of Science in User-Centered Design requires that students complete seven required courses and three electives, totaling 10 courses (30 credits).

Required Courses

• RUCD 101 - User Experience Design
• RUCD 120 - Human Factors Psychology
• RUCD 130 - Information Architecture
• RUCD 140 - Research Methods
• RUCD 150 - Design Ideation and Prototyping
• RUCD 170 - Design Operation and Leadership
• RUCD 190 - Capstone in User-Centered Design

Electives (choose three)

• RCOM 202 - Communication for Effective Leadership
• RDMD 160 - Ethics in Digital Design and Marketing
• RPJM 113 - Negotiating and Conflict Resolution
• RPJM 130 - Demystifying Agile Project Management
• RSAN 101 - Foundations of Data Science and Analytics
• RSAN 110 – Strategic IT Leadership: Powering Digital Transformation for Enhanced Global Performance, Growth, and Sustainability through Business Intelligence and Analytics
• RSAN 120 - Statistics and Data Analysis
• RSEG 161 - Web Development Technologies
• RUCD 160 - Information Visualization
• RUCD 175 - Inclusive Design & Digital Accessibility
• RUCD 180 - UX Design Processes
• RUCD 185 - Design of Non-Screen User Experiences
• RUCD 290 - Special Topics in User-Centered Design
• RUCD 292 - Internship in User-Centered Design

Program Outcomes

Upon completion of this program, students will be able to:

• Master interaction design and information architecture tools and techniques, including prototyping at various levels of fidelity.
• Understand and apply the human factors (including physical and psychological principles) that impact user interactions with digital products and technologies.
• Conduct and leverage qualitative and quantitative research to inform design decisions and evaluate designs.
• Adapt user experience processes and methods to a range of organizational contexts and settings.
• Develop design thinking, collaboration, and leadership skills necessary to plan and drive UX strategy for products and organizations.

Graduate Certificate in Healthcare Analytics

A four-course, 12-credit certificate on healthcare analytics.

Program of Study 

The Graduate Certificate in Healthcare Analytics is a 12-credit, four-course program.

Students must take the following:

• RHAN 100 Healthcare Database Fundamentals
• RHAN 110 Foundations of Healthcare Analytics
• RHAN 120 Data Mining and Visualization in Healthcare
• RHAN 130 Predictive Modeling in Healthcare

Graduate Certificate in Genomics

A four-course, 12-credit certificate covering bioinformatics sequence analysis, including bioinformatics scripting skills and basic next-gen sequencing analysis.

Program of Study

The Graduate Certificate in Genomics is a 12-credit, four-course program.

Students must take the following:

• RBIF 100 Bioinformatics Scripting and Databases with Python
• RBIF 102 Molecular Biology, Genetics, and Disease
• RBIF 109 Biological Sequence Analysis
• RBIF 111 Biomedical Statistics with R

Program Outcomes

Upon completion of this program, students will be able to:

• Perform biological sequence analysis leveraging Python, R, and common bioinformatics data sources
• Apply and validate bioinformatics data models using large genomic datasets
• Analyze and apply basic NGS analysis towards identifying biological insights and drug discovery

Graduate Certificate in Cheminformatics

A four-course, 12-credit certificate on cheminformatics, enabling the successful student to script in Python, and perform basic structural bioinformatics and cheminformatics analyses.

Program of Study

The Graduate Certificate in Cheminformatics is a 12-credit, four-course program.

Students must take the following:

• RBIF 100 Bioinformatics Scripting and Databases with Python
• RBIF 102 Molecular Biology, Genetics, and Disease
• RBIF 101 Structural Bioinformatics
• RBIF 110 Cheminformatics

Program Outcomes

Upon completion of this program, students will be able to:

• Gain skills in python, Pymol, and Knime for performing cheminformatics and data analysis tasks
• Understand the biological and biophysical bases of disease intervention by molecular medicines
• Learn to train and validate machine learning models for cheminformatics-based drug discovery

Graduate Certificate in Drug Discovery

A four-course, 12-credit certificate on drug discovery.

Program of Study

The Graduate Certificate in Drug Discovery is a 12-credit, four-course program.

Students must take the following:

• RBIF 100 Bioinformatics Scripting and Databases with Python
• RBIF 101 Structural Bioinformatics
• RBIF 106 Drug Discovery & Development
• RBIF 111 Biomedical Statistics with R

Program Outcomes

Upon completion of this program, students will be able to:

• Gain basic proficiency in python and R for bioinformatics and data analysis tasks
• Understand the biological and biophysical bases of disease intervention by molecular medicines
• Understand the role of informatics in the drug discovery and development process, including target ID, lead optimization, DMPK profiling, safety assessment, biomarker development, clinical trials, and commercial assessment.

Listed below are courses of instruction for the Rabb School of Continuing Studies, Division of Graduate Professional Studies. Online courses are presented in 10 discrete weekly modules.

Courses are available to all students qualified to take them. Course prerequisites are listed on the GPS website. When course prerequisites are not met, access to some courses may be provided following instructor or program chair approval.

Generally, a course is offered with the frequency of every semester, every year, every second year, every third year or every fourth year. The university reserves the right to make any changes in the offerings without prior notice.

This course is a high-content introduction to scripting and programming with applications in bioinformatics. It is appropriate for students with little previous programming experience. The course covers the fundamentals of working with Linux systems, using bioinformatics tools, and manipulating biological data files. The focus will be on scripting with Bash and Python. The course will also touch on topics such as how to interact programmatically with SQL databases and RESTful web services, and how to work with distributed compute systems to perform large calculations.

In this intensive course students will investigate the interrelationships existing amongst protein sequence, structure, and function through the lens of a structural bioinformaticist. Topics covered range from analysis of protein structure to domain classification, phylogeny, structural modeling, interaction site prediction, kinetics and thermodynamics of biomolecular interactions, and structure-based drug design. Throughout the course students will be exposed to software tools utilized by structural bioinformaticists in their daily work.

This course is an exploration of current research in molecular biology and genetics with a focus on human disease. Students are expected to already have familiarity with university level biological concepts. Topics to be covered will include: genetic mapping and genome wide association studies, cell signaling, control of gene expression, epigenetics, RNAi, developmental biology, apoptosis, immunology, virology, and cancer.  Students will learn to read and critique primary research articles. In addition, students will be introduced to relevant experimental techniques and how these techniques are applied in biomedical research.

There are high expectations for bioinformatics to contribute to drug discovery. This course explores issues faced during drug discovery and development. Topics include the drug discovery process, its major players and its origins; scientific principles behind drug properties and actions; target product profiles; disease and drug target selection, sources of drug-like molecules; assays and screening; medicinal chemistry; pharmacology; toxicology; and clinical trials.

Computational systems biology is a field that aims to provide an integrative, system-level understanding of biology through the modeling of experimental data. The course covers interacting systems by defining the basic structures of the biological network that allow a living cell to maintain homeostasis under different conditions and perturbations.

This course provides a foundation in biological sequence analysis, including methods for handling next-generation sequencing data. Topics include genomic assembly and variant detection using short reads, methods for homology detection, functional annotation of sequences, and use of databases and visualization tools.

This course covers small molecule data science, and modeling at the molecular level. We will introduce digital representations of molecules early on, and the first half of the course will cover topics in basic macromolecular structure and thermodynamics relevant to prediction and analysis of macromolecular interactions, and includes crystallography, energetics of hydrogen-bonding and hydrophobic interactions, and structure-based docking. The second half of the course will dive deeper into the basics of cheminformatics, covering chemical structures, chemical descriptors, and methods for clustering and similarity-searching for compounds.

This course is an advanced mathematics and applied statistics course that will introduce students to data analysis methods and statistical testing. It provides a foundation for Biological Data Mining and Modeling (RBIF 112) and Design and Analysis of Microarray Experiments (RBIF114). The course covers R (a statistical programming language) to introduce students to descriptive and inferential statistics, basics of programming, common data structures and analysis techniques. The course covers methods important to data analysis such as t-tests, chi-squared analysis, Mann-Whitney tests, correlation and regression, ANOVA, LDA, PCA, tests of significance, and Fisher's exact test.

The development of new bioinformatics tools typically involves some form of data modeling, prediction or optimization. This course introduces various modeling, prediction, and machine learning techniques including linear and nonlinear regression, principal component analysis, support vector machines, self-organizing maps, neural networks, set enrichment, Bayesian networks, and model-based analysis.

Transcriptomic studies are routinely used in genomic studies to detect changes in mRNA expression levels and have been key in developing biomarkers for several diseases. These experiments have fundamental statistical and data processing challenges associated with them. This course covers the statistical aspects of experimental design, biological and technical replicates, preprocessing, quality assessment, parametric and non-parametric statistical tests, multiple-hypothesis testing, P-value correction and false discovery rates, visualization techniques (e.g. heatmaps, volcano plots), and biological significance (e.g. functional annotation, pathways, hypergeometric tests, gene set enrichment).

This course covers methods in statistical genetics used to detect disease or quantitative trait loci in experimental and human populations. Basic concepts in Genetics, Genomics and Genetic Epidemiology are reviewed, with an emphasis on the statistical and practical issues involved in genetic analysis. Both linkage and association approaches will be covered, with a focus on applications in the human genome wide association (GWAS) setting for both SNPs and CNVs. Approaches to extracting and enriching GWAS through genotype imputation, GSEA, meta-analysis and genetics of gene expression analysis will also be covered, along with topics relevant to pharmacogenetics and techniques to analyze next generation sequencing data in a population setting.

This course introduces students to basic research in computational biology. The student and instructor will propose a novel research project with the goal of publishing their findings in a peer-reviewed journal. The scope of the project will be well defined and will be completed within one term. The instructor will oversee all aspects of the project and will provide appropriate scientific guidance and mentorship. The student will perform the research and will present their research to faculty at the end of each term. Research topics include but are not limited to scientific programming, software development, genome analysis, structural bioinformatics, evolution, drug discovery, and systems biology.

This course enables students to build on their critical thinking skills and apply oral and written communication strategies to solve organizational problems and drive organizational change. Students will develop, execute, and measure strategies applicable to a wide range of industries. Topics include negotiation and facilitation; crisis communications and public relations; virtual and global communications; and stakeholder management.

This course introduces students to the inner workings and challenges facing our global economy, and considers the ways that technology impacts these issues. Students explore the financial crisis of 2008 and how it led to the emergence of the FinTech industry. Students analyze current events in the global economic environment with respect to causes, responses and what can be learned. Students identify and examine the major global economic challenges of the near future, and identify potential technology solutions.

This course addresses the evolution of the financial industry landscape, the challenges and opportunities this new era presents, and the drivers behind the change. Students analyze case studies of well-known FinTech companies and discuss/debate value propositions, competition, business models and technology. Students examine recent trends and explore areas that are ripe for disruption in the industry.

Professionals in the FinTech sector must be versed in the domains and vocabularies of their business. This course will examine the various components of financial accounting and reporting, how this information is used, as well as what elements are reported and why. Students examine various accounting reports and financial statements to identify risks. Students identify technology pitfalls and solutions regarding financial reporting and interpretation.

This course introduces students to the exciting world of FinTech innovation and FinTech startup financing options. Students explore the options of venture capital investments (crowdsourcing, self-funding, etc.) and develop the skills needed to pitch their products. They learn how to identify competitors and develop the skills necessary to make sound financial decisions. Students come to understand financing from the perspective of both the investor and the entrepreneur.

This course enables students to develop the key skills necessary to lead product development initiatives and how to operate at the intersection of technology, customers, and the business. Discover how to construct a digital product by synthesizing industry trends, unmet customer needs, and technology capabilities.  Apply the product design and development process to determine product/market fit, iterate on product features, and develop metrics to track product outcomes.

This course focuses on developing and implementing business strategies for the technology industry. Students use case studies to assess the internal and external environments of both established and emerging firms; incorporating economic, technological, sociopolitical and legal trends to evaluate a firm's opportunities and threats. Students debate firms' strategic decisions in the context of a technologically innovative ecosystem, and analyze how those strategies represent or do not represent a fit between the external environment (e.g., industry, competition, etc.) and a firm's internal capabilities/competitive advantage. Students learn how to develop competitive advantage and assess competitive positioning.

Software based products and services, whether they are in finance and other domains, rely on programmers to build and maintain them. In this course, we will develop programming and problem solving skills using Python programming language while building software solutions inspired by use cases in the fintech industry.

If you are new to programming and software development, this course will demystify the processes, tools and technologies that programmers use to build these products and services. It will also assist in acquiring requisite skills to be an effective contributor to software development process. If you already have programming background, you will find yourself architecting and implementing software based solutions for real world Fintech problems and guiding others during various stages of development of these solutions.

This capstone course provides students the opportunity to exhibit their cumulative knowledge, skills and creativity related to FinTech, allowing them to pitch their products to business leaders.

In this course you will learn the origins of the digital marketing channel, how it’s transformed the way customers interact with brands and products, as well as how marketers leverage the different digital channels to optimize sales, awareness, and engagement goals. You will also come away with a deeper understanding of how marketing teams function based on different KPIs for a real-world company or organization.

Provides an overview of Search Engine Marketing (SEM) and Search Engine Optimization (SEO) including organic, local, and paid results. Course content investigates applications to both B2C and B2B businesses with a focus on technical considerations for achieving high search results and effective return on investment (ROI) for paid listings. Special topics covered include keyword development, landing page optimization, programmatic advertising, implications of AI and Machine Learning, and the future of Search.

This course provides detailed information about how to write copy and messaging for various digital formats. Special attention is given to differences in form factor, audience targeting, and SEO (search engine optimization) implications of various types of content. Content marketing tactics are explored in detail.

The Multichannel Marketing Campaigns course is set up as a strategic and practical guide to designing, conducting and measuring multichannel marketing initiatives ' for B2B and B2C brands. The course is designed to teach the fundamentals of 21st Century Digital Marketing ' based on creating on-going, seamless customer experiences across digital and traditional channels. Included in the foundational topics covered in this class are the three stages of marketing: The New Customer Journey, and Why the Marketing Campaign is dead; Developing customer journeys ' the fundamentals; Content, Channels and Measurement for Consumer Journeys. In addition, this course will look at the principles of paid, owned, and earned as converged digital marketing, and the role of diagnosing the channels for acquiring new customers.

Digital marketing is a broad field that encompasses more than just acquiring new customers to your product or service. In Conversion Rate Optimization, you will learn how to improve the customer journey and reduce friction throughout the funnel. You will learn best practices to streamline signup flows, improve onboarding, nurture leads, and increase customer lifetime value. At the end of this course, you should have a better idea of how to handle digital touchpoints for both prospects and customers that have raised their hands to express interest in your product or service.

Digital Imaging, Video and Media Production introduces students to the basics of digital and audio production. By engaging students around concepts of digital storytelling, this course examines how brands are using digital media across online platforms ' from social media to blogs and websites ' to tell stories that engage audiences and convert consumers. Through lectures and hands-on projects, students will gain competency in digital imaging and video editing and learn how to apply these skills to design, and build compelling creative for brand and performance marketing campaigns.

This course presents ethical dilemmas in digital marketing and works through the implications of various actions, such as tricking search engines (typically called 'black hat' techniques), posing as customers in social media, making false or exaggerated claims, and using questionable or sneaky channels (e.g. popups and plugins). In this course, we will explore several issues or concepts in depth, first introducing the facets and aspects of the topic, then utilizing that knowledge to develop our principles and values through dialogue and the examination of multiple perspectives.

Designed to provide students with an understanding of the challenges of collecting and maintaining electronic health data. The course focuses on issues specific to health data and the systems implemented to collect and store it. This includes an overview of various types of hospital systems; methods used to interface between systems; and operations issues typical of hospital systems. The course also includes a study of the evolving health care regulatory environment and common classifications for health care data. By the end of the course, students will be able to evaluate and identity health care data set problems and implement EHR-based solutions to the source data.

Gives students an overview of the history, concepts, purpose, and building blocks of healthcare analytics. Topics will include data acquisition and management, data analysis and visualization, and storytelling with data. Using case studies and other applied assignments, students will learn how to use statistical techniques to plan, deliver, and improve healthcare services, interpret data to make evidence-based decisions, and visualize large amounts of data to generate reports that tell a story. Given the rapidly advancing nature of the field, the course will touch on the latest technologies for healthcare data analytics. This course will also prepare students to begin work on the healthcare analytics capstone project, to be completed by the end of the program.

Among the most promising developments in data analytics is the growth in Data/Information Visualization. Across numerous disciplines, tools and techniques are emerging that help people interactively analyze and understand the flood of data now available. There is rapid growth in the availability of tools and also in the number of domains in which these techniques are deployed, including healthcare.

Visualization can tap into the ways in which health professionals rapidly and intuitively process information, taking advantage of IT tools to move beyond tabular displays and simple graphs. The theory and techniques of data visualization not only make information accessible, but also can open paths to exploration of cause and effect.

This course provides an overview of the field of data visualization, presenting current theory and best practices to students. We will rely heavily on hands-on learning, developing skills in Tableau and R. Although we naturally will use particular software, the lessons are aimed at principles so that students can continue to refine their skills as new tools emerge. Students will learn to evaluate and assess existing visualizations as well as develop their own information-rich interactive displays.

Teaches theory and best practices of modern healthcare analytics with attention to classification and prediction models. We cover preparation, visualization, and exploration of data and provide hands-on experience with the main methods of data mining and machine learning. In working with RStudio and R packages, students will become experienced in the creation of accurate models, as well as professional communication of their analytic results.

Some of the most important recent innovations in healthcare analytics are rooted in the fields of data mining and machine learning. In this course we will study a variety of major techniques currently applied to healthcare data, always in the context of real problems, and the search for actionable results. We will regularly move between theory and practice, working through the challenges of coding and managing data sources in a flexible yet efficient manner.

This course serves as an introductory course in the Health and Medical Informatics curriculum. The focus is on health and medical informatics as a discipline and includes the coverage of major healthcare policies and standards that affect the health information industry, patient care systems (computerized patient records, delivery and monitoring systems), and modeling concepts and applications. Students will explore the impact of Information Technology (IT) on healthcare and analyze real applications of health informatics. Other topics include: healthcare system reform/accountable care, mobile health devices, telehealth and HIEs. This course also provides the opportunity for students to explore their own interests in sub-specialties of health informatics through a research project that will be shared and reviewed by other students in the class at the end of the semester.

This course is designed to provide current and aspiring health/medical IT professionals with an understanding of the challenges of collecting and maintaining electronic health data. The course focuses on issues specific to health data and the systems implemented to collect and store it. This includes an overview of various types of hospital systems; methods used to interface between systems; and operations issues typical of hospital systems. The course also includes a study of controlled medical vocabularies typically used to define various types of health data as well as a survey of existing and evolving government driven standards and regulations.

This course addresses security, privacy, and compliance issues as they impact health information systems. The course explores and evaluates the moral and ethical concepts of information security. Students will explore security issues including restricted access and physical security of hardware/software along with the evaluation of information security tools. The course covers health data integrity, risks, and audit ability techniques along with regulatory compliance, confidentiality and privacy of patient data. The overall goal of the course is the evaluation and implementation of security in health information systems.

This course is designed to familiarize students with the different types of healthcare data, assure the quality of the data and how to understand and communicate the information provided in support of effective decision making by the various stakeholders of the healthcare system. Study and discussion topics will include how to choose the correct information for different decisions and communicate its meaning to users. Students will evaluate statistical methods and tools. The difference between research databases and operational databases will be covered along with techniques to effectively communicate quantitative healthcare data using tables and graphs. Methods for choosing the right medium will be explored in depth.

The healthcare delivery system in the U.S. is complex and in order to navigate it successfully students must have a fundamental understanding of the events and policies that have shaped the current environment in which they will be working. In addition to providing an overview of how the U.S. system has developed, this course will place a substantial focus on how healthcare data has developed over time and the ways in which it has informed the changes to the delivery system.

Offers students an opportunity to understand various legal concepts and issues present in a health care environment such as a hospital or health provider’s office. Topics covered will include statutory and case law applicable to medical records and some of the regulatory infrastructure for such records. We will discuss the importance of electronic data in medical practice, institutional healthcare information systems, and the inter-institutional record systems. We will also cover some of the risks, benefits, and challenges related to this data. The course will cover some of the situations which indicate the need to consult legal counsel.

This course is an introduction to healthcare business systems and models with a particular emphasis on the value of IT to the organization. This includes departmental design and management, capital and operating budgets, the budget planning process, and infrastructure design and strategic planning. Other topics include evaluation of vendors, vendor selection, purchase agreements and contracts, writing an RFP, analyzing an RFP response, clinical administration systems, and the design and management of integrated delivery networks.

This course will focus on the challenges facing the healthcare CIO/director with respect to organizational structure, alignment with enterprise strategy, portfolio management and regulatory compliance. In addition the course will look at how the application of IT can transform healthcare delivery in the current environment.

The U.S. healthcare system is in the midst of a period of unprecedented change. Population health management (PHM) focuses on the improved management of groups of patients through the assessment of various levels of risk and the development of care management frameworks to improve outcomes and reduce expenses. This course will examine the impacts of PHM on healthcare IT systems including: engaging primary care physicians in the hospital workflow; data interoperability both inside and outside of the enterprise; patient engagement; analytics for risk assessment and operational efficiencies; EHR workflows for PHM; and tools for long term care management.

This course is designed to introduce the student to risk management in the enterprise with a focus on the specific needs and challenges of the healthcare industry. This includes an overview of how risk is identified and planned for in healthcare organizations, how risk is financed, the basic principles of insurance, and what metrics allow risk to be measured and monitored.

Cloud computing is ubiquitous. Understanding Cloud and adding value in the migration, implementation, auditing and management of Cloud solutions and service models is the frontier of today's security leader. Increasingly our role is demanding advisory guidance and insight to groups such as Legal, Procurement, and Senior Executives. Being conversant in SaaS, PaaS, IaaS is no longer an option but is now a requirement, and integrating Cloud knowledge into a security program and security leadership will demand a multifaceted understanding of the technical, the managerial, and the business objectives. The focus of this course is to provide insight into:
' Cloud definitions and service models
' Cloud risk assessment and auditing
' Cloud security and controls
' Data governance and management
' Cloud contract management and managed service provider management
' Legal and regulatory considerations
Our goal is a comprehensive view on Cloud that will enable the security leader to become fluent in assessing, negotiating, managing, controlling and reporting upon Cloud value and Cloud data protection in their organization.

Network security is a broad term that can refer to the security of devices that comprise the network infrastructure, the traffic sent over that infrastructure, the hosts (clients and servers) attached to the infrastructure, the applications that utilize the network, the user community and the policies that govern usage of that network.

In this course, we will use the first four layers of the OSI protocol stack (physical, link, network, and transport) to introduce many aspects of network security. In particular, we will consider how devices at each layer provide 'defense in depth' by securing communications traffic as well as preventing unauthorized access. Our examination will be enhanced by using various security tools to observe network traffic that illustrates how security can be applied throughout today's enterprise.

This course introduces students to the foundational learning experience design methodologies and models commonly utilized in the design and development of digital learning experiences, training modules, or programs. Students explore the application of evidence-based learning science to learning experiences course development through methodologies grounded in learning experience design practices. Participants examine the roles and responsibilities of learning experience designers as they relate to the online learner, instructor, subject matter expert, and others. Throughout the course, students will apply design principles and collaborate to design and create prototypes; write measurable learning outcomes and related assessments; create and curate appropriate learning resources; integrate task analyses; and design activities that foster learning communities and promote collaborative learning environments.

This course introduces students to the technologies, systems, and toolsets commonly used to support the design, delivery, and assessment of synchronous and asynchronous online learning and training. Students explore the various types of platforms that support instructional design and online learning activities, including learning management systems (LMS), personal learning networks (PLN), open learning networks (OLN), content management systems, and others. Students will explore and evaluate a broad range of open and proprietary tools to support online instructional design, including communication and collaboration tools, assessment engines, electronic portfolios, rapid e-learning authoring tools, and others. Students will assess the capabilities of various instructional technologies to determine their efficacy in resolving online instructional challenges, and will investigate new and emerging tools.

This course will introduce students to Learning Management Systems (LMS) as the primary content authoring tool for online instructional design. Students will compare the feature sets of a number of LMS platforms, and evaluate best practices and workflows for authoring within such systems. Students will explore methods for course facilitation using LMS-driven tools, and examine how the LMS can support both synchronous and asynchronous approaches to online learning. Then, as course creators, students will work in teams and use an LMS to author and build their own online course content. Through hands-on practice, discussion, and critique, students will practice applying sound instructional design practices in tool selection; effective course design; and facilitation of a collaborative and constructive learning environment.

This course will explore the theoretical underpinnings and practical applications of learning experience design. Through collaborative solution development, students will apply cognitive and learning sciences to enhance learning comprehension. They will include in their practice the incorporation of accessibility and universal design for learning (UDL) principles. Students will also examine the process and techniques for data gathering and evaluation applicable for the purpose of driving iterative decision making and will explore a number of advanced assessment techniques to evaluate achievement of outcomes and competencies. This course will emphasize strategic LXD project leadership and advanced instructional design techniques key to fostering the development of healthy online learning communities in educational or corporate settings, including formal and informal personal learning networks.

This course provides students the opportunity to apply best practices in the management of complex online instructional design projects, including the initiation, planning, execution, monitoring, and closure of instructional development projects, including practical techniques to develop and manage scope, budgets, schedules, quality, resources. The course will explore the application and integration of both traditional and agile project management practices to existing online instructional design and development methodologies. Students will analyze and demonstrate both the project management and business analysis responsibilities associated with the instructional development project life cycle.

This practicum course provides students the opportunity to exhibit their cumulative knowledge, skills, and creativity related to online instructional design and technology. Students will demonstrate their ability to integrate design, pedagogical and technological principles and skills by applying them to a real-world project. Students will serve in a consulting capacity, and work independently or in small groups with a subject matter expert or client on a real project. Alternately, students may create a solution for an existing case study on an e-learning project that requires assessment, design, development, project management, and evaluation. Through development of an actual online instructional design project/product, the practicum allows students to experience the application of the skills and knowledge they have acquired in the prerequisite courses, and will result in the development of a high-quality portfolio project.

Adaptive and game-based elearning is a rapidly emerging trend in online learning for higher education and corporate training, as institutions and organizations transition from traditional methods of learning and assessment to more engaging, personalized, and interactive learning models. This course provides students with an opportunity to explore the tools and techniques utilized to design and develop these interactive learning experiences. Students will examine how adaptive learning techniques, technologies, and platforms can be utilized to support personalized and customized learning and training, and how traditional approaches to delivery of instructional materials and strategies can be modified and enhanced to deliver adaptive and game-based elearning in the online environment. Students will have the opportunity to apply the theories of adaptivity and gamification to the planning, storyboarding, and prototyping of an adaptive learning game or interactive module.

This course provides you the opportunity to practice using your choice of creative course-authoring tool(s) to plan, design, develop, and evaluate interactive multimedia learning experiences. You will apply principles and best practices to the creation and consumption of both static learning materials, such as data-driven infographics, slide presentations, and job aids; and dynamic content, such as video, audio podcasts, animations, interactive lessons, learning games, and simulations. You will gain a firm understanding of the rich science underpinning the creation of excellent multimedia learning experiences. At the end of the course, you will share your results in the RIDT 170 Virtual Multimedia Gallery available to all MS, LXD students and faculty.

The collection and analysis of data has dramatically altered how decisions are made and resources are allocated in a variety of industries. In online instructional design and technology, learning analytics are emerging tools to improve how online students learn, and how employees are trained through data-informed course design and instructional practices. This course will provide students an opportunity to explore learning analytics and how they can be deployed in various contexts in the online instructional design and technology field. Students will explore the implications of learning analytics in their organizations, and evaluate how it relates to concepts such as educational data-mining and academic analytics. The toolsets and methodologies, ethics and privacy considerations, and the systemic impact of learning analytics on institutions and organizations will be explored. Students will evaluate the present state of data analytics for instructional design, and assess possible future directions of the field. Students will apply the concepts presented in the course to analyze, plan, and deploy small-scale learning analytics pilot projects.

This course serves as an introductory course in the Technology Management curriculum, spanning the wide range of technologies in use in modern organizations. The course covers the major issues involved in selecting and deploying particular technologies based on the requirements of a particular project. The course provides a foundation for future study in strategic deployment of information technology in support of the business.

This course examines strategic operational issues from the perspective of the CIO or IT Director, exploring how IT organizations can best be managed. The course explores best practices for deploying limited financial and human resources for optimal results.

This course looks at strategic issues for the IT organization within the context of the larger organization and the relationship between the two. The course is designed to help current and future IT directors/CIOs effectively exploit information systems technologies within the context of a company's business needs.

This course provides an opportunity for students to focus on leadership and the applicable skills needed to function as a leader in an organizational setting. The course looks at leadership as a process by which one person influences the attitudes and behaviors of others. It looks at leadership of organizations and groups, including teams. Concepts covered include various leadership theories and models, leadership across cultures, leadership ethics and attributes, organizational change/development, and, the role of the leader in establishing organizational culture and facilitating change. The course encourages self-assessment through group projects and leadership simulations.

There are significant challenges to be found in managing today's technology professionals including the rate at which the knowledge on which they draw changes, their goals and incentives, and the way in which project teams comprised mostly of technical professionals can "age." This course focuses on issues that are of special interest to those managing technology professionals including analysts, developers, technical specialists, and infrastructure support personnel. We also discuss the importance of organizational structure, the ways it can affect performance, and the criteria upon which it should be chosen. Also included is an examination of organizational cultures, a contrast and comparison of various organizational structures, and managing stress in the constantly changing IT environment. Through assignments, case studies and class exercises, students will examine management practices and techniques regarding organizational structure, cross-functional teams, performance planning and enhancement, reward systems, recruiting, retention, and the development of knowledge workers.

In a world increasingly dependent on the effective exploitation of technologies, driving a sustainable competitive strategy is dependent upon organizations fostering a climate of innovation and creativity. This course aims to provide students with competencies and analytic skills to investigate technological challenges within dynamic organizational contexts. Students will research, evaluate and apply appropriate change management processes and innovative solutions to achieve strategic objectives and competitive advantages.

Crisis and contingency management are essential practice areas for technology leaders. Organizations have many moving parts and rely on many facets including people, processes, and technology to achieve their goals. Regardless of the perceived level of preparedness, a crisis or contingency event will affect the whole organization and that organization's customers. How a technology leader approaches the planning, practice, and execution of crisis and contingency management may determine how quickly and completely an organization weathers such an event and can even set that organization ahead of its competition.

The field of Technology Management is continually evolving. This Special Topics course facilitates the introduction of cutting-edge practices and technologies as they are introduced in the industry.

Projects today are the means for introducing innovation and implementing an organization's strategy, and project management is a discipline to deliver value. In this course, students will study the foundational principles and concepts that are applicable to a wide variety of projects. The course will explore the predictive (traditional) as well as agile approaches to managing projects. Using a real life-like case study in which an organization addresses a business problem by launching a new project, students will have an opportunity to walk in the shoes of a project manager as the project goes through the stages of initiation, planning and execution. Working individually as well as in groups, students will apply the tools and techniques that they have learned and experience first hand the challenges of working in teams solving complex project problems.

Projects attempt to achieve maximum value for minimum cost, and they often compete with other projects and operations within the organization for resources and financing. This course covers recently developed methods and value based metrics that, properly applied, can significantly impact project and portfolio value and revenue. By quantifying each side of the classic Triple Constraint Triangle, the value returned by the project and its contribution to the organizational portfolio can be accurately assessed and optimized. The course focuses on the project as an investment, and addresses both the theoretical and practical skills necessary to successfully manage that investment. Techniques covered include Estimated Monetary Value of the project scope; critical path and precedence diagramming methods of scheduling; resource optimization; and decision-making processes that optimize both project performance and return on investment.

This course covers risk management processes and techniques in depth, exploring the systematic and iterative approaches that encompass risk planning, identification, qualitative analysis, quantitative analysis, response planning, and monitoring and control. The course addresses risk management principles consistent with the PMBOK. Techniques for building and applying a risk management toolkit are explored, as are methods to implement risk management programs within an organization.

Conflicts of interest are common in project and program management, business environments, and daily life. This course provides a framework to understand the basis of conflict, to select an appropriate conflict resolution strategy, and to employ tactics that optimize results for both individuals and organizations. Characteristics of negotiation explored include the two fundamental strategies of negotiation; frames of reference; value creation; value claiming; and the impact of both tangible and intangible factors on the negotiation process. With globalization of project management and the implementation of virtual teams, the challenges to successfully resolve conflicts become increasingly complex. Approaches to conflict resolution differ among collocated and virtual teams, and cultural differences, interests, and values influence negotiation strategy and tactics. As each element of the conflict resolution process is explored, the course highlights special considerations for virtual team members. By participating in this course you will come to recognize the pervasiveness and importance of negotiation. You will acquire a new repertoire of negotiating skills. You will develop a systematic and positive approach to negotiating with colleagues, bosses, clients, other stakeholders, and external groups of all kinds--in ways that equip you to deal also with all kinds of conditions and circumstances.

The Project Management industry has grown immensely over the last ten years, and its trajectory is not slowing down.  As a result, the skill-set that Project Managers bring to the table is becoming more and more desirable to leaders, customers, project team members, subject matter experts, and stakeholders of all kinds.  Project Management is both a science and an art, and with both come specific challenges that Project Managers consistently face throughout the project lifecycle.

This course will examine those various challenges that more often than not arise within projects lifecycle, threatening project success.  The course gives students the opportunity to analyze the reasons these challenges occur and solutions for anticipating, preventing, minimizing and/or mitigating them. Because the primary source of many of these challenges are related to people, process, and communication, the course will focus heavily on these three elements, while also leaving room for additional challenges that may stem from different sources.

Successful Project Management requires people to excel in collaboration, facilitation, and communication.  Therefore, this course’s activities will vary between individual reading, group discussions, individual assignments, and collaborative team assignments.  Students should be ready to be on camera, collaborate with their fellow classmates to identify and analyze the challenges presented, and get creative with resolutions for the issues that arise as a result of these challenges.

Programs connect a company's strategic plans to the projects necessary to implement them. Programs frequently span many years, include multiple product releases, involve numerous and diverse stakeholder groups, and necessitate the establishment of a program office. This course covers the history, current practice, and future directions of program management.

This course covers the procurement process in depth, including concepts, principles and ethics, pricing methods, awards, and all phases of contract administration from both the seller and buyer perspectives. It explores the development of bids and requests for proposals; the evaluation of responses; and the capabilities and use of various types of contracts and pricing mechanisms. It addresses outsourcing (including market investigation, key risks, requirements definition and evaluations using performance based service agreements) and the evaluation and use of contract information systems.

This course examines the people-related aspects of project management across several areas, including team and stakeholder management; the role of the project manager in relation to the different levels, positions and personalities among the team and stakeholders; and the vital aspect of communications in effective project management. Also covered is the importance of project leadership vs. management, and an in-depth examination of the many people-related issues that often arise during the project lifecycle.

Agile project management techniques are being applied within a growing number of companies of various sizes and industries, from the entrepreneurial to the conservative. This course covers characteristics and delivery frameworks for agile project management. The course also explores how agile methods differ from traditional project management, along with how to recognize projects that may be suitable for agile techniques. Additional topics include the values, roles, deliverables, and practices of Scrum; additional agile and iterative methods; scalability and enterprise-wide considerations.

Agile approaches are being utilized in a myriad of projects, startups, and business units throughout the corporate world. This course takes the basics of Agile and sharpens this knowledge by demonstrating techniques to implement Agile practices in teams, projects, and the enterprise. We will first take a deeper dive into Agile techniques and practices that help teams create value. We will then study how Agile at scale creates an Agile enterprise where innovation teams collaboratively work with plan based approaches to deliver better results at the enterprise level. Students will be able to carry tools with them that will not only help in delivering innovative solutions in an Agile environment, but also help them coach teams and organizations to embrace Agile approaches.

All projects are investments. An investment is the act of allocating money, time, or effort to a particular initiative, or asset in order to achieve a profit or positive result.

Managing Projects as Investments is a course where students will learn concepts related to understanding how to define and measure projects and their performance. While most companies analyze and track investments at the portfolio level, this course will help students understand how to measure it at the project level to provide program and portfolio managers more accurate performance insights.

Throughout the course, students will learn more advanced methods to manage and measure success across the triple constraint. This advanced review will include critical path analysis, resource scheduling and leveling, earned-value-based techniques such as the schedule performance index (SPI) and earned schedule tracking, and other innovative measurements such as:

- Critical Path Drag  The amount of time by which each item on the critical path (activity, constraint, or bottleneck) is delaying the end of the project or, alternatively, the amount of time by which the project schedule could be compressed by reducing the duration of any critical path item to zero.

- Devaux’s Index of Project Performance (DIPP)  an innovative project management index used to measure project investment returns.

- Cost of Leveling with Unresolved Bottlenecks (CLUB) The cost to a project or program in reduced expected project prot (EPP) due to the delay caused by a specific resource bottleneck.

This course provides a foundation of the history, concepts, purpose and application of both data science and analytics in a business environment. This includes the methods of data collection, preparation, analysis, visualization, management, security, and preservation of large sets of information. Also covered in the course are the primary methods of analytics, including predictive, prescriptive, and descriptive. The course will examine the various uses of analytics and how these methods identify and leverage competitive advantage in the era of ever-growing information requirements.  Through Python programming for beginners and real-world public datasets, some business problems will be analyzed in this course. Tools such as Pandas, Jupyter Notebooks, or Spyder are used to identify and understand relationships in data and visualize information. The course will offer opportunities to create expressive data science projects while utilizing case studies, trends, techniques, and best practices in the data science field.

Business Intelligence can be described as the process of transforming data into knowledge. This transformation involves the use of processes and applications to extrapolate meaning from a company's data. This meaning usually ends up on dashboards, so that senior management can monitor assumptions and key performance metrics that are part of long-term planning cycles. As Business Intelligence processes mature, they begin to focus on using data to gain new insights. We call these processes Business Analytics, and this information is the key to Strategic Decision Making. This course provides students the opportunity to develop an in-depth understanding of the modern uses of business intelligence processes. Many companies now commonly use analytics to bridge the gap between existing business intelligence processes and current day needs. Students will be able to understand the business goals and objectives driving these needs. The course also explores the importance of various types of information systems and infrastructure as a framework for business decision making.

This course presents fundamental principles of statistics in the context of business-related data analysis and decision making, including methods of summarizing and analyzing data, statistical reasoning for learning from observations (experimental or sample), and techniques for dealing with uncertainties in drawing conclusions from collected data. Topics covered include applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.

This course will focus on the topic of big data and its management, including the tools and techniques designed to effectively analyze and visualize big data for strategic advantage. The course will cover definitions and concepts related to the areas of big data, strategic analytics, and data visualization; the overall problem of big data and the tools and techniques designed to manage it; and the ways in which strategic analytics and visualization can be utilized in different fields and industries to have a strategic impact on an organization's competitive advantage in today's business environment. The course will also address the future path of big data management, analytics and visualization, including career options and outlook.

This course will provide an introduction to advanced analytics and measurement in the areas of social networking and media, web and marketing analytics. The topics covered include the history, tracking, performance, optimization, metrics, analysis, visualization, decision making, reporting and best practices in each of those three areas. E-commerce will also be covered as it relates to web and marketing.

This course will provide an overview of data governance, including building a governance infrastructure with  organizational management, roles and responsibilities, stewardship, governance communications, regulatory  compliance, privacy concerns, data security, and risk management. Data quality will be addressed as a  continuous issue in data management, and the challenge it poses as the volumes of data increase and the uses  for data expand. This course will utilize case studies, trends, techniques, and best practices as it examines the  topics of data quality and data governance.

This course will focus on the fundamentals of predictive analytics as it relates to improving business performance. The course will cover predictive models, key modeling techniques, scoring, non-parametric regression and classification, principal components analysis and dimension reduction, time series, quality control methods, multiple predictor variables, and decision trees. The course will utilize best practices and case studies to illustrate how predictive analytics can facilitate educated decision-making to reduce costs, increase revenues, and provide competitive advantage across a variety of industries.

Organizations are experiencing unprecedented change due to the new realities of the digital world. Data now drives decisions in organizations more than ever before. Organizations have more data than they have ever had before, and more ways to analyze it are presented every day. Yet strategic initiatives continue to fail as often as they have in the past. Clearly a new approach to this issue is necessary. This course will cover an integrated approach to strategic management decision making, incorporating a thorough and realistic treatment of its relevance and its challenges. The course also covers how to plan and adopt big data analytics solutions through comprehensive planning, strategy development, and analysis.

This course will provide an overview of data security, privacy concerns, and ethics. The areas where information technology and privacy and ethics meet will be covered. Throughout the course, students will learn how to identify and assess the challenges inherent in data security and privacy, and the effectiveness of data security controls are discussed. This course will utilize case studies, trends, techniques, and best practices as it examines the latest technology impacting data security, privacy, and ethics in cyberspace. The course will touch on the virtual security, data security, and ethics in virtual worlds like Metaverse environments, and cover security and challenges of cryptocurrency wallets, and exchanges.

This course covers principles and concepts of agile project management in alignment with the needs of strategic analytics projects. Agile project management techniques take into consideration the values, roles, deliverables, and practices of Scrum; additional agile and iterative methods; scalability and enterprise-wide considerations. Concepts covered include process groups from initiation through closure; techniques for estimating and reporting; and management of risk, quality, resources, and communications. The dynamic nature of analytics projects, which include data warehouse implementations and business intelligence solutions, are characterized by uncertain or changing requirements and high implementation risks.

The field of Strategic Analytics is continually expanding and makes the news both national and globally every day. This Strategic Analytics Special Topics course facilitates the introduction of cutting-edge data practices'particularly around big data--as they are introduced in the industry. This course will cover new standards and practices as they are introduced, novel approaches and refined existing methodologies, and updated industry data and case studies on the most recent developments and practices in the area of Strategic Analytics.

This course explores advanced topics of Java programming language, including object- oriented programming concepts; exceptions; generic programming and annotations; collections; Java foundations classes (JFC); delegation event model; layout managers; swing components including panels, menus, toolbars, and text components; multi-threading; streams and input/output programming; networking; and Java database connectivity (JDBC).

This course provides a solid foundation of C++ with focus on object-oriented concepts and programming techniques. Concepts covered include classes, objects, abstract data types, file processing, inheritance, encapsulation, polymorphism, overloading, reuse, and templates.

This course examines major aspects of the Spring Framework. The Spring Framework can be used in developing any Java application, but it is especially effective for building Web and Enterprise Java applications (JEE). Spring is the most popular application development framework for the Web Enterprise Java. Millions of developers around the world use Spring Framework to create high performing, easily testable, reusable Web and Enterprise Applications.

Object-oriented modeling and design form the foundation of many software projects today and are pre-requisites to developing in C++, Java, and other object-oriented programming languages. This course covers object modeling and design techniques as they are applied from the point the high-level project requirements are established, through high level and detailed design, to the point where implementation is ready to start. The course focuses on Unified Modeling Language (UML), an approach that combines previously competing object modeling theories, as well as concepts including distributed object frameworks; design patterns; existing object-oriented languages such as C++ and Java; and lifecycle and maintenance issues of object-oriented applications.

This course covers non-programming related aspects and best practices of the software development process, from requirements engineering, architectural design, and quality management to software maintenance and process improvement. Concepts addressed include software engineering tools, models, and methodologies; requirements engineering and specifications; system modeling; business process analysis; VORD and Use Case analysis; control and distribution models; estimating and scheduling; risk management; software maintenance and improvement; and ethics within the industry.

This course provides an introduction to theory, tools and techniques needed by software release engineers. It is intended to give students the skills to evaluate and use tools for continuous integration and delivery (DevOps).

This course provides an opportunity for students to work collaboratively on a complex software project. Organized in teams, students will analyze a software problem, develop requirements, designs, test plans, and deliver code. Students will synthesize skills learned in the core courses of the Software Engineering program to deliver a significant project, under the guidance of faculty.

This course introduces user interface design principles and concepts of user-centered design. User interface concepts for web, desktop and mobile applications are practiced in a variety of design projects. Universal design concepts, accessibility design, navigational schemas and elements of screen design are also discussed.

This course covers topics related to software testing methodology, with a focus on realistic, pragmatic steps for testing consumer and business software. Concepts covered include test cycles; testing objectives; testing in the software development process; types of software errors; reporting and analyzing software errors; problem tracking systems; test case design; testing tools; test planning; test documentation; and managing a test group.

This course provides hands-on experience with functional programming'a style of programming that has seen increasing popularity due to its ability to work with complex concepts through highly adaptable models. Functional programming supports higher-level abstractions, customizable data structures, as well as concurrency and parallelism inherent in cloud computing and big data analytics. Students will use functional extensions of Java and a popular functional programming language Scala to apply functional programming approach to a variety of design, modeling and implementation challenges.

This course provides an extensive examination of the following Web Development Technologies used in developing web applications: HTML5, Cascading Style Sheets (CSS3), Responsive Web Design, Modern JavaScript, React JS.

Design Patterns form an advanced area in object oriented design and architecture. Design patterns focus on solutions to problems commonly found in design of object oriented programs. The first part of the course examines the fundamentals of the core patterns: creational, behavioral, structural, and system patterns.

This course provides an in-depth, hands-on study of building microservices applications using Java, Spring Framework, Spring Boot, Docker, Swagger, Kubernetes. Microservices create small, distributed, and independent services that require careful design and implementation.  Spring Boot simplifies microservices application development. It removes the boilerplate code involved with writing a REST-based service. Docker containers help to pack, ship, and run any application as a lightweight, portable, self-sufficient container that can run virtually anywhere. Swagger provides an efficient way to document the REST APIs developed by Microservices.Kubernetes provides an efficient deployment, scaling, management of Microservices. Hands-on development projects will provide opportunity to apply Microservices technological capabilities to creation of Microservices Projects.

The data center is increasingly virtual. In this class, students will explore 'cloud'-based services, ranging from 'Software as a Service''using internet-based software suites such as Google Docs or Salesforce.com, through platform-based systems (PaaS) such as Microsoft's Azure environment that make it easy to focus on developing new apps or services, to complete cloud-based infrastructure (IaaS) such as Amazon's Web Services. The class also explores how use of the cloud also changes how we 'do' IT. Cloud-based services are especially well-suited to Agile development and Lean Startup thinking. This leads to new ideas such as DevOps and 'continuous deployment.' In addition, use of SaaS security systems changes how we integrate systems, how we handle identity and access management (IAM), opening up new threats'and new opportunities'to keep data secure. Finally, we will look at how the cloud enables us to work with more data than ever before, 'Big Data''NoSQL databases and scalable infrastructure (e.g., Hadoop). Students will learn how to evaluate the various cloud-based services and how to communicate that evaluation to decision-makers in the organization. There will also be a hands-on practicum using Amazon Web Services (AWS) and exploring the most common features of Infrastructure as a Service (IaaS), and how IaaS, overall, differs from older paradigms of systems management and program architecture.

Agile Software Development has evolved into a flexible software lifecycle model, framework, and set of development techniques that present an answer to challenges of developing software projects under tight timelines and changing requirements. This course will use a variety of software projects and case studies to define agile software development practices and the concepts of adaptive and evolutionary refinement, and to demonstrate how they can be used to deliver software projects. The course will examine best practices in applying agile software development techniques as a flexible response to changes. SCRUM framework, a popular methodology in Agile Software Development, will be examined and used in team projects, as a flexible methodology for self-organizing teams.

This course introduces students to user-centered design (UCD), design thinking, Lean UX, and associated methodologies. It is heavily focused on user research and user-centered design. Students will explore a range of UCD approaches while gaining practical experience creating portfolio-ready deliverables. The course will focus primarily on website & mobile user research and design.

This course will examine the psychological and social principles impacting human factors in physical and virtual environments. Students will explore biological, perceptual, and cognitive factors in the context of interface design and ergonomics. Human-centered design will play a central role in considering the cultural and social implications of design.

Information Architecture (IA) is defined as 'the art and science of organizing and labeling shared information environments (websites, intranets, online communities and software) to support usability and findability.' (source: iainsitute.org). This course balances theoretical grounding of IA with practical design work. We will cover principles of IA as a professional practice and how to design effective, research-supported, user-centered information systems. Students will understand and apply information organization concepts; design and apply appropriate assessment techniques for particular information environments; and develop strategies to effectively communicate design rationale and advocate for users.

Human-centered design depends on a deep understanding of user goals, needs, and behaviors that only user research can provide. This course will introduce students to key qualitative and quantitative research methodologies, including surveys, interviews, and usability testing. A range of research approaches will be covered, including moderated vs. unmoderated; formative, iterative, and summative; as well as lab, field and remote studies. Key statistical and ethical concepts will be explored in the context of applied research challenges.

The goal of this course is to build practical interaction design and problem-solving skills. Students will be exposed to a toolkit of methods for every stage of the design process, from brainstorming and sketching through prototyping at various levels of fidelity. Throughout the course, students will practice divergent and convergent thinking necessary to solve real world design problems within the context of a collaborative and user-centered process.

The goal of information visualization is to communicate information accurately and effectively to users, helping them to analyze and make decisions about data and evidence. The course will cover various data visualization theory and techniques, while providing students with the opportunity to apply them. Students will gain an understanding as to how humans visually perceive and make inferences from data graphics. They will experiment with various data models, graphical conventions, and tools as they design, innovate and evaluate data visualizations.

In this course students will learn the strategies for effective leadership of design teams and processes, particularly from an institutional/business perspective. Operational topics include: building effective teams; project management; cost analysis; and resource allocation. Leadership components include methods of leadership within the contexts of conception, design, implementation; and operational leadership for products, processes and systems.

The goal of universal design is to build products and interfaces that are usable and accessible to everyone, not just a small subset of normative or ‘average’ users. This course will provide an introduction to universal design for digital and physical accessibility. Students will gain an understanding of the range of physical, cognitive, contextual, and social disabilities that challenge technology users, and how inclusive design benefits everyone. Topics covered include accessibility guidelines, assistive technologies, plain language, and legal and ethical considerations.

This course will provide students with the industry skills and techniques required to work effectively on a user experience (UX) or product team in the context of different organizational environments. Students will explore a range of development processes (Agile, Lean, SAFe, and many others), and learn how UX design and user research fit into those processes. Coursework will focus on developing and applying communication and collaboration skills. Topics will include obtaining stakeholder and executive buy-in for UX resources, process change, and the integration of design thinking and design critique activities into product development processes.

The opportunities to develop innovative user experiences are no longer limited to web and mobile interfaces. This course will introduce students to challenges that extend beyond the digital screen, including design for services, devices, and emerging technologies. The service design portion of the course will focus on techniques for understanding context of use and designing cohesive experiences across multiple touch-points. The UI design portion will introduce tools for designing and testing specialized UIs for embedded systems, Internet of Things (IoT), voice, and immersive environments.

This seminar-style course is intended to bring together all of the prior knowledge and skills that the student has obtained. Students will work independently or in small teams to produce a prototype of a product or system. The process will be an iterative, semester-long project in which students (or small teams of students) will identify the purpose of the design; construct a set of wireframe documentation with justification for the design, capturing the up-front intentions behind the user experience; and mockup and/or prototype the UX with subsequent user testing that leads to a final prototype. With the exception of the final prototype, each part of the process will include peer reviews. A final presentation of the product will be the culminating activity, and will receive feedback from a program-curated group of industry experts.

The field of user-centered design is continually evolving. New technologies and research into human factors are continually introduced and evolving. This course facilitates the introduction of cutting-edge practices and technologies as they are introduced in the industry.

The Internship course provides students with an opportunity to learn and gain hands-on experience related to their individual career goals and/or field of study. There are many benefits in pursuing an internship, including valuable workplace experience, learning from professionals, meeting new contacts, and testing your "fit" in a field.
UX internships offer students the opportunity to apply the design and research skills they have mastered through UCD coursework. Students are responsible for securing the internship and the support of a site supervisor with a UX background who is willing to commit to actively mentoring them throughout the session. The internship has to have a specific focus on one or more aspects of user experience or an adjacent field (user research, UX design, service design, etc.). Students cannot earn internship credit through their current position/employer. Students must work at least 100 hours at the internship site, and complete a portfolio piece, reflection paper or case study based on their experience.
Students are limited to completing one internship for graduate credit as part of their Master’s degree. Internships must be secured by the student and approved by the chair at least 45 days prior to the start of the session. The internship must include a supervisor to whom you report for your work at the company or organization.