University Bulletin (2019-2020)

• Minor
• Major (BA/BS)
• Combined BA/MA
• Master of Science
• Doctor of Philosophy

Undergraduate Major and Minor

The undergraduate program in computer science teaches the theoretical fundamentals and practical aspects of computing, preparing students for creative jobs in the computer industry and/or for graduate school. In addition, our curriculum is a stimulating and useful preparation for a number of indirectly related professions, such as law, medicine, and economics.

Graduate Program in Computer Science

The graduate program in computer science is concerned with the fundamental concepts arising in the development and use of computing systems, including the study of computational complexity and information theory, the design and analysis of serial and parallel algorithms, the design of programming languages, systems, and artificial intelligence.

Graduate Program in Computational Linguistics

The graduate program in computational linguistics is concerned with the scientific study of language from a computational perspective. It is an interdisciplinary field, which draws on linguistic theory (phonology, syntax, semantics, and pragmatics) and computer science (artificial intelligence, theory of computation, and programming methods).

Undergraduate Major and Minor

The Association for Computing Machinery (ACM) has developed a curriculum for computer science that is published annually. Much of the attached text is copied and reworded from the text for Computer Science Curriculum 2008.

Objectives

Computing is a broad field that extends well beyond the boundaries of computer science, drawing its foundations from a wide variety of disciplines. Computer science increasingly plays a methodological role in other disciplines and the impact of technology is a significant subject of study in fields like political science and journalism.

Majors in computer science learn to utilize concepts from many different fields, integrate theory and practice, and appreciate the value of good engineering design. They develop a high-level understanding of systems as a whole and an appreciation for the structure of computer systems, and the processes involved in their construction and analysis, that transcends the implementation details of the various components. They attain an understanding of the theoretical underpinnings of the discipline and how that theory influences practice. Many recurring themes such as abstraction, complexity, and evolutionary change are encountered during their course of study. Students are also educated as engineers, learning how to design, develop and maintain, large complex software systems and applications, integrating them into workplaces, and developing interfaces to them that support human use. Given the rapid continuous development of the field, majors are educated to be lifelong learners.

In recognition of the increasing significance of computer science as an important discipline for many students throughout the university, the department also offers a selection of courses relevant to students majoring in other disciplines or students double majoring in computer science and another concentration. Several courses enable students to develop skills and understanding of web technology and the impact of the Internet on society. Other courses provide students with the relevant skills and knowledge for assessing the adoption of new technology within an organization. Non-majors can learn the computing and modeling skills that support their work in their core discipline. Students in the social sciences can learn how the skills and methods from their core discipline are relevant for the development of user friendly technology, or the introduction of technology into the workplace.

Skills

Majors in computer science will develop a number of skills.

1. Understanding the elements of computational thinking.
2. Understanding the trade-off involved in design choices.
3. Identifying and analyzing criteria and specifications appropriate to specific problems, and planning strategies for their solution. Analyzing the extent to which a computer-based system meets the criteria defined for its current use and future development.
4. Deploying appropriate theory, practices, and tools for the specification, design, implementation, and maintenance as well as the evaluation of computer-based systems.
5. Specifying, designing, and implementing computer-based systems.
6. Evaluating systems in terms of general quality attributes and possible tradeoffs presented within the given problem.
7. Applying the principles of effective information management, information organization, and information-retrieval skills to information of various kinds, including text, images, sound, and video.
8. Awareness of security issues. Exposure to issues associated with access, encryption, and networking.
9. Applying the principles of human-computer interaction to the evaluation and construction of a wide range of materials including user interfaces, web pages, multimedia systems and mobile systems.
10. Learning to deploy effectively the tools used for the construction and documentation of software, with particular emphasis on understanding the whole process involved in using computers to solve practical problems.
11. Awareness of the existence of publicly available software (such as APIs or open source materials). Effective engagement in open-source projects. Exposure to effective software reuse.
12. Operating computing equipment and software systems effectively.

Additional skills prepare the majors for success as professionals:

1. Communication. Making succinct presentations to a range of audiences about technical problems and their solutions. This may involve face-to-face, written, or electronic communication.
2. Teamwork. Learning to work effectively as a member of a disciplinary or interdisciplinary development team.
3. Numeracy. Understanding and explaining the quantitative dimensions of a problem.
4. Self-management. Managing one's own learning and development, including time management and organizational skills
5. Professional development. Learning the skills necessary to continue one's own professional development after graduation.

Knowledge

1. Discrete structures
2. Programming fundamentals
3. Graphics and visual computing
4. Algorithms and complexity
5. Intelligent systems and Machine Learning
6. Data Compression
7. Computational Linguistics
8. Architecture and organization Bioinformatics
9. Operating systems, concurrency, and security
10. Artificial life
11. Distributed Computing and Networking Data management
12. Programming languages Software engineering(exposure to different programming paradigms)
13. Numerical methods, simulation and modeling
14. Human-Computer Interaction
15. Entrepreneurial Computer Science
16. Computer Supported Cooperative Work Internet and Society

Social Justice

The department does not currently offer a specific course to cover social and professional issues. However, many of these issues are distributed throughout the curriculum. Lifelong learning is a common theme of many of the elective courses. There are many opportunities for experiential learning and the development of oral communication and teamwork skills. Open software, freedom of information, patent and copyright law, software pirating, social inclusion and the digital divide, and the effect of the Internet on political discourse and free speech, are among the topics covered in the Internet & Society course.

Upon Graduating

The BS curriculum is intended for students who want to work as computer scientists in a technical firm or plan to attend graduate school in computer science. The BS requires more rigorous training in the analytic and engineering foundations of computer science. It includes a breadth component that exposes students to a range of topics within computer science, and it also includes a depth component that requires students to explore a sequence of courses in one area of computer science.

The BA requirement reduces the ACM curriculum to the basic set of skills and knowledge. Students graduating with the BA will be prepared to work as application programmers or in secondary areas related to computation like informatics or library science. The BA curriculum is also ideal for students who plan to use their degree in computer science as a basis for graduate study in a professional school or graduate programs in other areas of science or social science.

Graduate Program in Computer Science

Master of Science in Computer Science

Students graduating from the Master's program in Computer Science are expected to:

1. Attain programing and software engineering skills sufficient for building large scale applications and web-based applications.
2. Demonstrate a graduate-level understanding of at least two of three basic areas of computer science: systems, artificial intelligence and applied interdisciplinary computer science, and theory.
3. Follow the social, legal, and ethical behaviors of the field and its practice.
4. Be prepared to enter the job market.

Doctor of Philosophy in Computer Science

Students graduating with a Ph.D. in Computer Science are expected to:

1. Attain research expertise and complete a significant body of original research that advances a specific field of computer science.
2. Communicate fundamental knowledge of their field of research, as well as details of their own research, in both written and oral form, to expert and non-expert audiences.
3. Teach computer science topics effectively, for those interested in teaching careers.
4. Be competitive for appropriate positions in industry and academia.

Graduate Program in Computational Linguistics

Master of Science in Computational Linguistics

Students who graduate with the M.S. in Computational Linguistics (CL) are expected to:

1. Attain programming competency and familiarity with theory and algorithms sufficient for carrying out work in the research and development of modern CL applications.
2. Demonstrate a foundational understanding of data structures, discrete mathematics, and probability and statistics, within computer science (CS).
3. Demonstrate foundational competency in and knowledge of the techniques used within theoretical syntactic and formal semantic analysis and investigation, within linguistics.
4. Attain competency and familiarity with corpus creation and analytics, as well as the design and implementation of the machine learning algorithms and techniques used in CL.
5. Attain the skills needed to allow further learning and growth in areas of knowledge and skills used within CL, CS, and linguistics.
6. Follow the ethics of appropriate behavior of the field and its practice.
7. Be prepared to enter the job market in CL, or to begin PhD studies in CL, CS, or (for students who entered with prior study of the field) linguistics.

It is recommended that students have completed the courses COSI 10a and COSI 12b by the end of their sophomore year since they are prerequisites for advanced courses in the major.

In order to declare the major or minor students must have completed COSI 12b and COSI 21a with a passing grade of C+ or better. Upon completion of these courses, students must fill out the form declaration (see https://www.brandeis.edu/computer-science/undergraduate/advising-faqs.html) and schedule a meeting with the Undergraduate Advising Head (UAH).

The requirements are listed below and include many options. Students can schedule an appointment with the UAH for further information.

The general requirements for admission to the Graduate School, given in an earlier section of the Bulletin, apply here. Applicants for admission to the computer science program must submit three letters of recommendation and are encouraged to take the Graduate Record Examination. Funds from research grants and fellowships are available to provide financial support for well-qualified students. GREs are required for Computer Science graduate students.

Timothy Hickey, Interim Chair
Scientific visualization. Groupware. Interval arithmetic and constraints. Programming languages.

Richard Alterman, Director of Graduate Studies (on leave spring 2020)
Computer-supported cooperation. Learning and technology. Cognitive engineering and modeling. Communication and discourse. Intelligent user interfaces.

Mitch Cherniack
Databases. Software engineering. Programming languages.

Antonella DiLillo, Undergraduate Advising Head
Algorithms. Image and video processing. Computer vision. Scientific computing.

Pengyu Hong
Computational biology. Image processing. Statistical machine learning.

Hongfu Liu
Data mining. Machine learning and related applications in social media. Computer vision and bioinformatics.

Harry Mairson
Logic in computer science. Lambda calculus, type theory, and functional programming. Algorithms and complexity.

Sophia Malamud
Linguistics. Formal semantics and pragmatics of natural languages.

Olga Papaemmanouil
Distributed data management. Databases. Large-scale networked systems.

Jordan Pollack (on leave academic year 2019-2020)
Artificial intelligence. Evolutionary computation. Artificial life.

James Pustejovsky
Artificial intelligence. Computational linguistics. Qualitative spatiotemporal reasoning. Lexical semantics. Corpus linguistics.

Pito Salas
Applied Computer Science. Software Engineering, architecture and design. Development methodology, Scalability. Software Entrepreneurship. Robotics.

Liuba Shrira (on leave academic year 2019-2020)
Operating systems. Distributed systems. Long-lived storage systems.

James Storer (on leave spring 2020)
Data compression and image processing. Computational geometry. Parallel computing. Algorithms.

Nianwen Xue
Linguistic structures. Language processing. Natural computational linguistics.

The minimum requirements for the computer science minor are six courses:

1. COSI 12b and 21a.
2. Four additional computer science courses. Only one cross-listed course may be counted toward the elective requirement. COSI 98a may only be used once as an elective. No COSI course numbered 10 or lower may be used toward the minor.
3. No course with a final grade below C- can count toward fulfilling the requirements for the minor in computer science.
4. No course taken pass/fail may count toward requirements for the minor.

Students with no prior programming experience must satisfactorily complete COSI 10a prior to enrolling in COSI 12b. Students may be exempted from COSI 10a if they either: 1) received a score of 5 on the AP Computer Science A exam (AP Computer Science Principles test does not currently replace any COSI courses), or 2) successfully complete the online placement exam.

Required of All Majors

Foundational Literacies: As part of completing the Computer Science major, students must:

• Fulfill the writing intensive requirement by successfully completing one of the following: COSI 12b, COSI 21a, or COSI 131a and providing documentation of the software they develop in core Computer Science courses with programming assignments. Software documentation explains how the software operates as well as how one can use it. It can be embedded in the source code of the software or be provided as a standalone document (or combination of the two). Software documentation is a critical part of software engineering and requires good technical writing skills.
  Students will submit documentation for all programming assignments they submit in the core courses and receive feedback on each one. This ensures that students will have an opportunity to improve their technical writing skills in the subsequent assignments.
• Fulfill the oral communication requirement by successfully completing: 2-credit practicum COSI 45a in the fall or spring of senior year.
• Fulfill the digital literacy requirement by successfully completing one of the following: COSI 12b, COSI 21a, or COSI 131a. 

Degree of Bachelor of Arts

The minimum requirements for the Computer Science major include 9.5 courses:

1. Four core courses: COSI 12b, 21a , 29a, and 131a.
2. Electives: At least five additional COSI courses. Only one cross-listed course may be counted toward the elective requirement. COSI 98a may only be used once as an elective. COSI 99d and COSI courses numbered 10 or lower may not be used toward the major.
3. 2-credit practicum COSI 45a taken in the fall or spring of senior year to fulfill the oral communication requirement.
4. No course with a final grade below C- can count toward fulfilling the requirements for the major in computer science.
5. No course taken pass/fail may count toward requirements for the major. 

Students with no prior programming experience must satisfactorily complete COSI 10a prior to enrolling in COSI 12b. Students may be exempted from COSI 10a if they either: 1) received a score of 5 on the AP Computer Science A exam (AP Computer Science Principles test does not currently replace any COSI courses), or 2) successfully complete the online placement exam.

Degree of Bachelor of Science

The minimum requirements for the Computer Science major include 14.5 courses:

1. Six core courses: COSI 12b, 21a, 29a, 121b, 130a and 131a.
2. Mathematics courses: Math 8a (MATH 36a, ECON 83a, BIOL 51a, or PSYC 51a may substitute for MATH 8a) and MATH 10a.
3. 2-credit practicum COSI 45a taken in the fall or spring of senior year to fulfill the oral communication requirement.
4. Electives: at least six additional COSI courses. Only two cross-listed courses may be counted toward the elective requirement. COSI 98a may only be used once as an elective. COSI 99d and COSI courses numbered 10 or lower may not be used toward the major.
5. No course with a final grade below C- can count toward fulfilling the requirements for the major in computer science.
6. No course taken pass/fail may count toward requirements for the major.

Students with no prior programming experience must satisfactorily complete COSI 10a prior to enrolling in COSI 12b. Students may be exempted from COSI 10a if they either: 1) received a score of 5 on the AP Computer Science A exam (AP Computer Science Principles test does not currently replace any COSI courses), or 2) successfully complete the online placement exam.

Honors

Graduation with honors in computer science requires completion and defense of a senior honors thesis. Students interested in senior thesis should contact prospective faculty mentors by the spring of their junior year and should take note of the prerequisites for enrollment in COSI 99d (Senior Research).

Available only to Brandeis students who have completed all requirements for the undergraduate Bachelors degree and have performed well in the computer science major and have completed three 100-level COSI electives in addition to those required for their undergraduate degree. Students should apply in their senior year, at which time they should propose a course of study for the fifth year that typically consists of six graduate-level courses of which at most three may be chosen from the following courses: COSI 152aj, COSI 152bj, COSI 153aj, COSI 153bj, COSI 154aj, COSI 293aj, COSI 210aj, COSI 200a,b and COSI 210a.

The five-year BA/MS or BS/MS degree program in Computational Linguistics is designed for outstanding undergraduate students who will have completed all requirements for the undergraduate BA or BS degree within four years at Brandeis, with a major in either Language and Linguistics and/or Computer Science. Eligibility for the program is normally limited to students who have maintained a minimum 3.500 GPA in all linguistics and computer science courses taken. Students complete the MS in Computational Linguistics by taking computational linguistics courses in the senior (fourth) year and in one additional (fifth) year of study. The MS degree provides a solid foundation for professional work in the field of computational linguistics or for additional graduate study in computational linguistics and/or theoretical linguistics. An application should be submitted no later than May 1 of the student's junior year.

Program of Study

Students admitted to the program must fulfill the following requirements, in addition to completing their undergraduate degree: a schedule of course work designed in conjunction with and approved by the director of graduate studies consisting of twelve courses. Among these twelve, all students are required to complete LING 131a, COSI 114b, COSI 134a, COSI 137b, COSI 138a, COSI 140b, and at least one of the computational linguistics internship course COSI 293b or the computational linguistics master's thesis course COSI 299a. The master’s thesis must be deposited electronically to the Robert D. Farber University Archives at Brandeis. Depending on student background, at the determination of the director of graduate studies, the remaining five courses may include required foundational courses in computer science and/or linguistics; electives; or a blend of the two.

Residence Requirement

The minimum residence requirement is one year after completing the BA or BS degree.

Students may submit a written request to count a course from another department to satisfy one of the required computer science electives. Approval of such a request is based on the relationship of this course to the student's other computer science electives.

Master of Science in Computer Science

Program of Study

The MS program in computer science is a two-track program designed for outstanding students with undergraduate degrees in any field. Admitted students with an undergraduate degree in Computer Science must satisfactorily complete an approved schedule of nine courses, which includes:
A. Elective courses: At least nine COSI courses numbered 100 or greater of which at most three may be chosen from the following courses: COSI 152aj, COSI 152bj, COSI 153aj, COSI 153bj, COSI 154aj, COSI 293aj, COSI 210aj, COSI 200ab and COSI 210a.

Admitted students with an undergraduate degree in a field other than Computer Science must satisfactorily complete an approved schedule of twelve courses, which includes:

1. Three core courses providing fundamental background in Computer Science: COSI 12b, COSI 21a, and COSI 29a. At most two core courses can be taken a semester. Students must maintain a minimum average of a B+ in the 4 undergraduate courses required. At the end of each semester in the program, students who have an average of less than a B+ for the subset of these courses that they have taken thus far will be subject to probation or withdrawal from the program.
2. Elective courses: At least nine additional COSI courses numbered 100 or greater of which one must be COSI 131a; one may be chosen from the following courses: COSI 115bj, COSI 152aj, COSI 152bj, COSI 153aj, COSI 153bj, COSI 154aj, COSI 293aj, COSI 210aj, COSI 200ab and COSI 210a. Only one independent study or one JBS course may count as a 100 level elective. Students who have previously taken the equivalent of any core course may petition the Director of Graduate Studies for an exemption allowing them to substitute an additional COSI course numbered 100 or greater.

Students with no prior programming experience must satisfactorily complete COSI 10a prior to enrolling in COSI 12b. Students will be exempted from COSI 10a if they successfully complete the online placement exam.

Residence Requirement

The minimum residency requirement is three semesters.

Master of Science in Computational Linguistics

Program of Study

The two-year MS program in computational linguistics is designed for outstanding students, preferably with an undergraduate degree in either linguistics or computer science. The MS provides a solid foundation for professional work in the field of computational linguistics or pursuit of a PhD in computational linguistics and/or theoretical linguistics.

Students must complete a schedule of course work designed in conjunction with and approved by the director of graduate studies consisting of a minimum of twelve courses. Among these twelve, all students are required to complete LING 131a, COSI 114b, COSI 134a, COSI 137b, COSI 138a, COSI 140b, and at least one of the computational linguistics internship course COSI 293b or the computational linguistics master's thesis course COSI 299a, or the computational linguistics capstone project course COSI 295a. The master’s thesis must be deposited electronically to the Robert D. Farber University Archives at Brandeis. Depending on student background, at the determination of the director of graduate studies, the remaining five courses may include required foundational courses in computer science and/or linguistics; electives; or a blend of the two.

Residence Requirement

The minimum residence requirement is two years.

International Master's students need to complete two academic semesters in F1 status to be eligible to take COSI 293g, which counts for one academic credit. In the case that a student coming from another university in the U.S. with a year on an F1 visa is legally able to engage in practical training before the two semesters are up, such training must be approved by the Computer Science department as well as gain CPT authorization and is expected to be a continuation of a summer job or internship in a computer science oriented position. Please note that students may only take COSI 293g classes twice during their degree at Brandeis, and may want to delay until they have more computer science experience. For more information regarding Curricular Practical Experience, please refer to the ISSO CPT page.

Requirements for the Degree of Doctor of Philosophy in Computer Science

Adviser

Ph.D. students are expected to work closely with faculty on research projects of mutual interest. By the end of the second year, the student must obtain the consent of a computer science faculty member to serve as adviser and dissertation committee chair.

Course Requirements

Satisfactory completion of an approved schedule of nine computer science courses numbered 100 or above of which two may be chosen from the following courses: COSI 152aj, COSI 152bj, COSI 153aj, COSI 153bj, COSI 154aj, COSI 293aj, COSI 210aj, COSI 200a,b and COSI 210a. Students may petition the director of graduate studies to substitute courses from other departments that are relevant to their research area. Students who have obtained a Masters degree in Computer Science may petition to reduce their course requirements by a maximum of 6 courses.

Each summer, full-time PhD students are required to do work related to their research area under the supervision of a faculty member. The work can take the form of dissertation research, or can involve an industrial internship. Students doing dissertation research over the summer should register for CONT 250. Students doing an industrial internship must have the consent of their advisor and should register for COSI 393g.

Teaching Requirement

Teaching is a critical skill required in both academic and industrial careers that follow graduation. To prepare students for this role, students normally serve as teaching interns for one course per year. Teaching internship responsibilities may include assisting with course design and lecture preparation, giving an occasional class lecture, assignment formulation and grading.

Thesis Committee and Proposal

1. Establishment by the adviser and the director of graduate studies of a thesis committee consisting of the adviser, two other Brandeis faculty, and one or more appropriate external members from outside Brandeis.
2. An approved, written thesis proposal by the candidate that surveys the relevant literature and states the goals of the dissertation and topics to be investigated (including aspects already completed or underway), along with an oral presentation to the thesis committee that is open to computer science faculty who wish to attend.

Thesis Defense

Public defense of a completed dissertation will be announced three weeks in advance. Copies of the complete thesis will be available to the faculty during these three weeks.

Residence Requirement

The minimum residency requirement is three years.

Requirements for the Degree of Doctor of Philosophy in Computer Science with an Additional Specialization in Quantitative Biology

Program of Study

Students wishing to obtain the specialization must first gain approval of the Director of Graduate Studies. This should be done as early as possible, ideally during the first year of graduate studies. In order to receive the PhD in Computer Science with additional specialization in Quantitative Biology, candidates must complete (a) the requirements for the PhD described above and (b) the course requirements for the quantitative biology specialization that are described in the quantitative biology section of this Bulletin.

Any alteration to the quantitative biology course requirements must be approved by the Director of Graduate Studies and by the quantitative biology program faculty advisory committee.

COSI 10a Introduction to Problem Solving in Python
[ dl sn ]
Open only to students with no previous programing background. Students may not take COSI 10a if they have received a satisfactory grade in COSI 12b or COSI 21a. May not be taken for credit by students who took COSI 11a in prior years. Does not meet the requirements for the major or minor in Computer Science.
Introduces computer programming and related computer science principles. Through programming, students will develop fundamental skills such as abstract reasoning and problem solving. Students will master programming techniques using the Python programming language and will develop good program design methodology resulting in correct, robust, and maintainable programs. Usually offered every semester.
Staff

COSI 12b Advanced Programming Techniques in Java
[ dl sn ]
Prerequisite: COSI 10a or successful completion of the COSI online placement exam.
Studies advanced programming concepts and techniques utilizing the Java programming language. The course covers software engineering concepts, object-oriented design, design patterns and professional best practices. This is a required foundation course that will prepare you for more advanced courses, new programming languages, and frameworks. Usually offered every year.
Staff

COSI 21a Data Structures and the Fundamentals of Computing
[ dl sn ]
Prerequisite: COSI 12b. This course may be taken concurrently with COSI 12b with permission from the Undergraduate Advising Head or Director of Graduate Studies.
Focuses on the design and analysis of algorithms and the use of data structures. Through the introduction of the most widely used data structures employed in solving commonly encountered problems. Students will learn different ways to organize data for easy access and efficient manipulation. The course also covers algorithms to solve classic problems, as well as algorithm design strategies; and computational complexity theory for studying the efficiency of the algorithms. Usually offered every year.
Antonella DiLillo

COSI 29a Discrete Structures
[ qr sn ]
Covers topics in discrete mathematics with applications within computer science. Some of the topics to be covered include graphs and matrices; principles of logic and induction; number theory; counting, summation, and recurrence relations; discrete probability. Usually offered every year.
Staff

COSI 45a Effective Communication for Computer Scientists
[ oc ]
Prerequisite: One 100-level COSI elective. Yields half-course credit.
Teaches the basics of good oral communication and presentation, such as structuring a presentation, body language, eye contact, pace and appropriateness for the audience. It will cover, with practice, a range of speaking engagements majors might meet in academia and industry including: presentation of a research paper, software architecture proposal, business elevator pitch, research funding proposal, and so on. Students will present a project already created for a 100-level COSI elective. They will give the presentation in class, receive feedback based on the practices taught and then have a chance to give the presentation a second time. Usually offered every semester.

COSI 93a Research Internship and Analysis
Provides students with an opportunity to work in a computer science research lab for one semester, pursuing a project that has the potential to produce new scientific results. Students and the faculty member mutually design a project for the semester that supports the research agenda of the group. Students must attend all research group meetings and present their findings in oral and written form at the end of the semester. The project typically includes background research, some lab work, and collaboration with other group members. Course requires signature of the instructor, is subject to the availability of undergraduate research positions, and is typically open only to juniors and seniors.
Staff

COSI 97a Senior Field Project
Staff

COSI 98a Independent Study
Open to exceptional students who wish to study an area of computer science not covered in the standard curriculum. Usually offered every year.
Staff

COSI 98b Independent Study
Open to exceptional students who wish to study an area of computer science not covered in the standard curriculum. Usually offered every year.
Staff

COSI 99d Senior Research
Prerequisites: Open only to seniors. Submission of a thesis proposal during the spring semester of the junior year. This proposal must be signed by a faculty member who has agreed to supervise the thesis.
Research assignments and preparation of a report under the direction of an instructor. Usually offered every year.
Staff

COSI 101a Fundamentals of Artificial Intelligence
[ sn ]
Prerequisites: COSI 21a.
Survey course in artificial intelligence. Introduction to Lisp and heuristic programming techniques. Topics include problem solving, planning natural language processing, knowledge representation, and computer vision. Usually offered every year.
Jordan Pollack

COSI 102a Software Entrepreneurship
[ sn ]
Prerequisite: Sophomore standing. May not be taken for credit by students who took COSI 165a in prior years.
Covers the fundamental concepts needed to transform an idea for a software application into a viable IT business. The focus of the course is on software-based IT enterprises and the specific challenges and opportunities they present. Learn the "Lean Startup" process in this course with a significant hands-on focus. Usually offered every year.
Pito Salas

COSI 105b Software Engineering for Scalability
[ sn ]
Prerequisite: COSI 21a and either COSI 166b or permission of the instructor.
Covers some of the "big ideas" that come in to play when building large, complex, and highly scaled software systems. We will look at both research and practice scaling architecture and software design. How do you design and architect large scale web based systems? What are the classic algorithms and patterns used to achieve massive scale? We will look at caching, database partitioning, queueing, messaging and more. And we apply this learning working in teams of students to design and implement their own version of the Twitter backend from the ground up, and then stress test and measure it’s scalability using real world tools and technologies. Usually offered every year.
Pito Salas

COSI 111a Topics in Computational Cognitive Science
[ sn ]
Prerequisite: COSI 101a or 125a, or permission of the instructor.
Focuses on cognitive and social theories of activity that underlie human computer interaction and computer mediated collaboration. Topics include problem solving and skill acquisition, planning and situated activity, distributed cognition, activity theory, collaboration, communication, discourse, and interaction analysis. The laboratory work is designed to give the student practice with the ideas and techniques under discussion. The content and work of the course are specifically designed for an interdisciplinary class of students from computer science and the social sciences. Usually offered every second year.
Richard Alterman

COSI 112a Modal, Temporal, and Spatial Logic for Language
[ sn ]
Prerequisites: COSI 29a.
Examines the formal and computational properties of logical systems that are used in AI and linguistics. This includes (briefly) propositional logic and first order logic, and then an in-depth study of modal logic, temporal logic, spatial logic, and dynamic logic. Throughout the analyses of these systems, focuses on how they are used in the modeling of linguistic data. Usually offered every second year.
James Pustejovsky

COSI 114b Fundamentals of Computational Linguistics
[ sn ]
Prerequisites: COSI 12b and LING 131a, or permission of the instructor.
Provides a fundamental understanding of the problems in natural language understanding by computers, and the theory and practice of current computational linguistic systems. Of interest to students of artificial intelligence, algorithms, and the computational processes of comprehension and understanding. Usually offered every year.
Marie Meteer and James Pustejovsky

COSI 115bj Spoken Dialog Design
[ sn ]
Interactive applications have become ubiquitous around the world on phones and other devices. Since voice is the most natural medium for human communication, spoken dialog is becoming an essential part of the interface. However, creating an effective spoken dialog application requires more than just programming skills. It requires knowledge from many disciplines including linguistics, artificial intelligence, computer-human interaction, and computational linguistics. This course will bring together the essential elements of these fields and the software skills and tools required to build an effective dialog system and guide students through hands-on projects applying that knowledge to real applications. Offered as part of JBS program.
Marie Meteer

COSI 118a Computer-Supported Cooperation
[ sn ]
Covers basic theory and concepts of computer-supported collaborative work and learning. Laboratory work enables the student to practice a set of basic techniques as they apply to the development of computer-mediated collaboration. The content and work of the course are specifically designed for an interdisciplinary class of students from computer science and the social sciences. Usually offered every second year.
Richard Alterman

COSI 119a Autonomous Robotics
[ sn ]
Prerequisites: COSI 21a and one additional Computer Science elective.
Become part of the team developing “Campus Rover”, our long term project. Explore the fundamental “big questions” in robotics: How do robots know what to do? How do they see the world? How do they know where they are? How do they know where to go? How do they control their bodies? How should robots behave around people? How can we get them to work together? Learn and understand Robot Operating System (ROS) and how software for robots is built. Solve gradually more advanced robotic problems, work with real robots in our Robotics Lab. This is a hands-on course, emphasizing real world implementations. Usually offered every year.
Pito Salas

COSI 120a Topics in Computer Systems
[ sn ]
Prerequisite: COSI 21a.
Content will vary from year to year. May be repeated for credit. Prerequisites may vary with the topic area; check with instructor for details. Usually offered every third year.
Staff

COSI 121b Structure and Interpretation of Computer Programs
[ sn ]
Prerequisites: COSI 12b.
An introduction to idioms of programming methodology, and to how programming languages work. Principles of functional programming, data structures and data abstraction; state, imperative and object-oriented programming; lazy data structures; how an interpreter works; metalinguistic abstraction and programming language design; syntax analysis, lexical addressing, continuations and explicit control; continuation-passing style, metacircular and register-machine compilers. Usually offered every year.
Harry Mairson

COSI 123a Statistical Machine Learning
[ qr sn ]
Prerequisite: COSI 29a, MATH 10a, and MATH 15a.
Focuses on learning from data using statistical analysis tools and deals with the issues of designing algorithms and systems that automatically improve with experience. This course is designed to give students a thorough grounding in the methodologies, technologies, mathematics, and algorithms currently needed by research in learning with data. Usually offered every year.
Pengyu Hong

COSI 125a Human-Computer Interaction
[ sn ]
Prerequisite: sophomore standing.
Covers the basic theory and concepts of human-computer interaction. Topics include methodology for designing and testing user interfaces, interaction styles and techniques, design guidelines, and adaptive systems. The laboratory work is designed to give the student practice in a set of basic techniques used in the area of human-computer interaction. Usually offered every second year.
Richard Alterman

COSI 126a Introduction to Data Mining
[ sn ]
Prerequisites: COSI 12b and COSI 21a, MATH 15a or MATH 22a.
Introduces the basic concepts, principles, methods, and implement techniques of data mining for large-scale and big data analysis, with three data mining tasks: clustering, classification and association mining. Some basic concepts, tasks, relationships with statistics and machine learning are provided including unsupervised, supervised and semi-serviced learning. Usually offered every second year.
Hongfu Liu

COSI 127b Database Management Systems
[ sn ]
Prerequisites: COSI 12b or 21a and COSI 29a.
Introduces database structure, organization, and languages. Studies relational and object-oriented models, query languages, optimization, normalization, file structures and indexes, concurrency control and recovery algorithms, and distributed databases. Usually offered every second year.
Mitch Cherniack

COSI 129a Introduction to Big Data Analysis
[ sn ]
Prerequisite: COSI 12b. MATH 15a is recommended.
Provides the knowledge to use Big Data tools and learn ways of collecting, processing and analyzing massive amounts of unstructured data. This is an interdisciplinary course that will combine techniques from system design, distributed processing, machine learning and natural language processing to address big data analytic tasks. Usually offered every year.
Olga Papaemmanoil

COSI 130a Introduction to the Theory of Computation
[ sn ]
Prerequisite: COSI 29a. May not be taken for credit by students who took COSI 30a in prior years.
Formal treatment of models of computation: finite automata and regular languages, pushdown automata and context-free languages, Turing machines, and recursive enumerability. Church's thesis and the invariance thesis. Halting problem and undecidability, Rice's theorem, recursion theorem. Usually offered every year.
James Storer

COSI 131a Operating Systems
[ dl sn ]
Prerequisites: COSI 21a. May not be taken for credit by students who took COSI 31a in prior years.
Fundamental structures of a computer system from hardware abstractions through machine and assembly language, to the overall structure of an operating system and key resource management abstractions. Usually offered every year.
Liuba Shrira

COSI 132a Information Retrieval
[ sn ]
Prerequisite: COSI 21a, COSI 101a or COSI 114b.
Explores the theory and practice of textual information retrieval, including text indexing; Boolean, vector space and probabilistic retrieval models; evaluation; interfaces; linguistic issues; web search; QA and text classification. Students will implement algorithms and design and build a search-based application. Usually offered every second year.
Peter Anick

COSI 132b Networked Information Systems
[ ss ]
Prerequisite: COSI 131a.
Explores the fundamental concepts in design and implementation of networked information systems, with an emphasis on data management. In addition to distributed information systems, we will also study modern applications involving the web, cloud computing, peer-to-peer systems, etc. Usually offered every second year.
Olga Papaemmanouil

COSI 134a Statistical Approaches to Natural Language Processing
[ sn ]
Prerequisite: COSI 101a or COSI 114b. This course may be taken concurrently with COSI 114b.
An introductory graduate-level course covering fundamental concepts in statistical Natural Language Processing (NLP). Provides an in-depth view of the statistical models and machine-learning methods used in NLP, including methods used in morphological, syntactic, and semantic analysis. Usually offered every year.
Staff

COSI 135b Computational Semantics
[ sn ]
Prerequisites: COSI 12b or permission of the instructor. Open to advanced undergraduate students and first-year graduate students.
A study of the computational treatment of core semantic phenomena in language. After a review of first-order logic and the lambda calculus, the course focuses on three core topics: interrogative structures, including semantics of questions, question-answering systems, dialogue, entailment, commonsense knowledge; meaning update and revision; and computational lexical semantics. Usually offered every year.
James Pustejovsky

COSI 136a Automated Speech Recognition
[ sn ]
Prerequisite: COSI 114b, or COSI 12b and 121b, or permission of the instructor.
Explores speech recognizer core components and their underlying algorithms, surveying real applications. Covers phonetics, HMMs, finite state grammars, statistical language models, and industry standards for implementing applications, like VXML. Students build and analyze simple applications using a variety of toolkits. Usually offered every year.
Marie Meteer

COSI 137b Information Extraction
[ sn ]
Prerequisites: COSI 101a, COSI 121b, COSI 134a or permission of the instructor.
Examines the major issues and techniques in extracting semantically meaningful information from unstructured data, putting the information into a structured database for easy access and manipulation. Teaches students to design and implement a working natural language system. Usually offered every year.
Nianwen Xue

COSI 138a Computational Linguistics Second Year Seminar
[ sn ]
Open to students in the final term of the MS program in Computational Linguistics. Also open to PhD students in Computational Linguistics. Students in Computer Science MS or PhD programs may enroll with permission of the instructor.
A seminar on research methods, writing, and presentations, and in abstract writing. Aims to help students learn to prepare and deliver oral presentations and written papers of their research work, according to the standards used and expected in this field—both in industry job and academic settings. This will be useful to students applying for jobs in industry or for further graduate work at the Ph.D. level, as well as for the work carried out in such jobs and academic study. Usually offered every year.
Lotus Goldberg

COSI 139b Technology and the Learning Sciences
[ sn ]
Prerequisite: COSI 118a or COSI 125a.
The field of the learning sciences combines cutting edge cognitive research on learning and teaching with technological innovation. In this class students develop their skill and practice for design-based technological innovation as it applies to learning and education. Usually offered every second year.
Richard Alterman

COSI 140b Natural Language Annotation for Machine Learning
[ sn ]
Prerequisite: COSI 114b or LING 131a and concurrent enrollment in COSI 114b.
Studies corpus linguistics, the computational study of any naturally occurring fragment of language, a key area for data mining, information extraction, and machine learning. Students model, annotate, train, test, evaluate, and revise their own corpus for machine learning. Usually offered every second year.
James Pustejovsky

COSI 146a Principles of Computer System Design
[ sn ]
Prerequisites: COSI 131a and MATH 10a (MATH 10b recommended).
Topics on the design and engineering of computer systems: techniques for controlling complexity; strong modularity using client-server design; layering; naming; networks; security and privacy; fault-tolerant systems, atomicity and and recovery; performance; impact of computer systems on society. Case studies of working systems and readings from the current literature provide comparisons and contrast. Usually offered every second year.
Liuba Shrira

COSI 147a Distributed Systems
[ sn ]
Prerequisite: COSI 131a and C/C++/UNIX programming skills.
This course covers abstractions and implementation techniques for the design of distributed systems. Topics include: distributed state sharing, coherence, storage systems, naming systems, security, faulttolerance and replication, scalability and performance. The assigned readings for the course are from current literature. Usually offered every second year.
Liuba Shrira

COSI 149b Practical Machine Learning with Big Data
[ sn ]
Prerequisite: COSI 12b and MATH 15a.
In this experiential learning course, students will learn and practice machine learning techniques (such as regression, clustering, decision trees, support vector machines, assemble techniques, and deep-learning) to tackle real problems in industry and/or interdisciplinary research. Usually offered every second year.
Pengyu Hong

COSI 152aj Web Application Development
[ sn ]
Prerequisites: COSI 12b, or permission of the instructor.
An introduction to web programming that covers the fundamental languages and tools, including HTML/CSS for page layout, javascript/ajax for client-side integration, and server-side programming in javascript using Node/Express, Mongo, and MySQL. The course also discusses security, scaling/optimization, and multi-tier architectures. Offered as part of JBS program.
Timothy Hickey

COSI 153a Mobile Application Development
[ sn ]
Prerequisites: COSI 12b.
Introduces the design and analysis of mobile applications that covers the architecture of mobile devices, APIs for graphical user interfaces on mobile devices, location-aware computing, social networking. Also covers the theory and practice of space and time optimization for these relatively small and slow devices. Usually offered every second year.
Staff

COSI 154aj The JBS Incubator
[ sn ]
Prerequisite: COSI 12b, or permission of the instructor.
An introduction to software engineering for web and mobile applications. Covers agile programming techniques, rapid prototyping, source control paradigms, effective software documentation, design of effective APIs, software testing and analysis, software licensing, with an introduction to business plans for software entrepreneurs. Offered as part of JBS program.
Timothy Hickey and Marie Meteer

COSI 155b Computer Graphics
[ dl sn ]
Prerequisite: COSI 12b.
An introduction to the art of displaying computer-generated images and to the design of graphical user interfaces. Topics include graphic primitives; representations of curves, surfaces, and solids; and the mathematics of two- and three-dimensional transformations. Usually offered every third year.
Timothy Hickey

COSI 164a Introduction to 3-D Animation
[ dl sn ]
May not be taken for credit by students who took COSI 65a in prior years.
Covers the fundamental concepts of 3-D animation and teaches both the theory underlying 3-D animation as well as the skills needed to create 3-D movies. Students demonstrate their understanding of the concepts by creating several short animated movies. Usually offered every third year.
Timothy Hickey

COSI 166b Capstone Project for Software Engineering
[ sn ]
Prerequisite: COSI 21a.
Teaches modern software engineering concepts, emphasizing rapid prototyping, unit testing, usability testing, and collaborative software development principles. Students apply these concepts by building a complex software system in small teams of programmers/developers using current platforms and technologies. Usually offered every year.
Pito Salas

COSI 175a Data Compression and Multimedia Processing
[ sn ]
Prerequisites: Undergraduates and combined BA/MA students must complete COSI 21a, COSI 29a, and COSI 131a and received a B+ or better. Other graduate students should have a background that includes at least what is covered in these three courses.
A seminar studying research papers relating to data compression and information extraction / understanding from multimedia, including content based image and video retrieval, object recognition, data analytics, and related applications of machine learning. Usually offered every second year.
James Storer

COSI 177a Scientific Data Processing in Matlab
[ sn ]
Prerequisite: COSI 12b. MATH 15a is recommended.
Introduces scientific computing using Matlab. Programming concepts such as data types, vectors, conditional execution, loops, procedural abstraction, modules, APIs are presented. The course will present scientific techniques relevant to computational science, with an emphasis on image processing. Usually offered every second year.
Antonella DiLillo

COSI 178a Computational Molecular Biology
[ dl sn ]
Open to advanced undergraduate students and graduate students.
Information and computing technologies are becoming indispensable to modern biological research due to significant advances of high-throughput experimental technologies in recent years. This course presents an overview of the systemic development and application of computing systems and computational algorithms/techniques to the analysis of biological data, such as sequences, gene expression, protein expression, and biological networks. Hands-on training will be provided. Usually offered every other year.
Pengyu Hong

COSI 180a Algorithms
[ sn ]
Prerequisites: Undergraduates and combined BA/MA students must complete COSI 21a and COSI 29a, and received a B+ or better. Other graduate students should have a background that includes at least what is covered in these two courses.
Basic concepts in the design and analysis of algorithms. Usually offered every second year.
James Storer

COSI 190a Introduction to Programming Language Theory
[ sn ]
Prerequisite: COSI 121b or familiarity with a functional programming language, set theory and logic.
An introduction to the mathematical semantics of functional programming languages. Principles of denotational semantics; lambda calculus and its programming idiom; Church-Rosser theorem and Böhm's theorem; simply typed lambda calculus and its model theory: completeness for the full type frame, Statman's 1-section theorem and completeness of beta-eta reasoning; PCF and full abstraction with parallel operations; linear logic, proofnets, context semantics and geometry of interaction, game semantics, and full abstraction. Usually offered every second year.
Staff

COSI 200a Readings
Specific sections for individual faculty members as requested.
Staff

COSI 200b Readings
Specific sections for individual faculty members as requested.
Staff

COSI 210a Independent Study
Usually offered every year. May be repeated once for credit.
Staff

COSI 215a Advanced Topics in Computer Supported Cooperation
Topics vary from year to year. The course may be repeated with the approval of the instructor. Usually offered every second year.
Staff

COSI 216a Topics in Natural Language Processing
Prerequisite: COSI 101a or 112a or 114b.
Reviews recent trends in computational approaches to linguistics, semantics, knowledge representation for language, and issues in parsing and inferences. Usually offered every fourth year.
James Pustejovksy

COSI 217a Topics in Adaptive Systems
Prerequisite: COSI 101a.
In nature, systems with greater complexity than any designed by humans arise without a designer. The central question explored is: How can complex modular organization arise without an intelligent designer? The class reads about theories of organization in different settings and scales (cells, brains, minds, behavior, society, economies), and studies papers, models, and algorithms from a variety of fields that might shed light on the issue. Usually offered every third year.
Jordan Pollack

COSI 217b Natural Language Processing Systems
Prerequisite: COSI 101a or 112a.
This course looks at building coherent systems designed to tackle real applications in computational linguistics. Particular topics will vary from year to year, but each call will consider some of the following: machine (aided) translation, speech interfaces, information retrieval/extraction, natural language question answering systems, dialogue systems, summarization, computer-assisted language learning, language documentation/linguistics hypothesis testing, and handwriting recognition. Usually offered every year.
James Pustejovsky and Nianwen Xue

COSI 233a Discourse and Dialog
Prerequisite: LING 131a. Formerly offered as COSI 233f.
A critical element of interactive systems is managing the dialog between the system and the user. This course will explore multiple approaches to implementing dialog management components, both symbolic and statistical, including what contextual information must be represented in the dialog states and the decision processes to move from one state to another. Students will implement a dialog manager using industry standards. Usually offered every second year.
Marie Meteer

COSI 293b Computational Linguistics Research Internship
Permission of the graduate advising head required.
Offers graduate students a opportunity to engage in industrial research in computational linguistics by completing a paid or unpaid internship of at least ten weeks duration approved and monitored by a faculty member.
Staff

COSI 293g Master's Research Internship
Permission of the Director of Graduate Studies required. Yields quarter-course credit. May be repeated for credit. Intended for Master's students.
Offers graduate students an opportunity to engage in industrial research in computer science by completing a paid or unpaid internship of at least ten weeks duration approved and monitored by a faculty member. Usually offered every semester.
Staff

COSI 295a Computational Linguistics Capstone Project
Permission of the graduate advising head required.
Offers graduate students a opportunity to develop an independent project of original research as an active member of a computational linguistics research laboratory. Usually offered every year.
Staff

COSI 299a Computational Linguistics Master's Thesis
Permission of the graduate advising head required. May be repeated once for credit.
Staff

COSI 300a Master's Project
Usually offered every year.
Staff

COSI 300b Master's Project
Usually offered every year.
Staff

COSI 393g Graduate Research Internship
Permission of the Director of Graduate Studies required. Yields quarter-course credit. May be repeated for credit. For Ph.D. students only.
Offers Ph.D students an opportunity to engage in industrial research in computer science by completing a paid or unpaid internship of at least ten weeks duration and forty hours per week, approved and monitored by a faculty member. Usually offered every summer.
Staff

COSI 400d Dissertation Research
Specific sections for individual faculty members as requested.
Staff

ANTH 138a Digital Cultures
[ dl ss ]
This course offers a 2-credit optional Experiential Learning practicum.
Examines how anthropology can contribute to the understanding of new media as transformative social-cultural forces. Explores various forms of computer-mediated and digital communication (e.g., instant messaging, blogging, social media, on-line dating) and the ways in which people interact in these different contexts of cyberspace. Explores how new forms of digital technologies are shaping forms of identity, community and society today. Involves participatory research projects with a digital public-facing life. Usually offered every third year.
Brian Horton

LING 130a Formal Semantics: Truth, Meaning, and Language
[ hum qr ss ]
Prerequisite: LING 100a or permission of the instructor. LING 120b recommended.
Explores the semantic structure of language in terms of the current linguistic theory of model-theoretic semantics. Topics include the nature of word meanings, categorization, compositionality, and plurals and mass terms. Usually offered every year.
Sophia Malamud

LING 131a Introduction to Natural Language Processing with Python
[ dl ]
Prerequisite for undergraduate students: LING 100a and COSI 10a or equivalent prior programming experience to be determined by permission of the instructor.
This is an upper-level course on the computational properties of natural languages and the fundamental algorithms used for processing them. The main objectives of the course are to develop a through understanding of the principles and formal methods used in the design and analysis of language processing algorithms, and to provide an in-depth presentation of these algorithms as they are applied to Lexical, Morphological, Syntactic, and Semantic analysis. Usually offered every year.
Nianwen Xue

MATH 15a Applied Linear Algebra
[ sn ]
Prerequisites: MATH 5a and permission of the instructor, placement by examination, or any mathematics course numbered 10 or above. Students may take MATH 15a or 22a for credit, but not both.
Matrices, determinants, linear equations, vector spaces, eigenvalues, quadratic forms, linear programming. Emphasis on techniques and applications. Usually offered every semester.
Keith Merrill (fall), Staff (spring)

MATH 36a Probability
[ qr sn ]
Prerequisite: MATH 20a or 22b.
Sample spaces and probability measures, elementary combinatorial examples. Conditional probability. Random variables, expectations, variance, distribution and density functions. Independence and correlation. Chebychev's inequality and the weak law of large numbers. Central limit theorem. Markov and Poisson processes. Usually offered every fall.
Staf

MATH 39a Introduction to Combinatorics
[ sn ]
Prerequisite: COSI 29a, MATH 23b, or permission of the instructor.
Topics include graph theory (trees, planarity, coloring, Eulerian and Hamiltonian cycles), combinatorial optimization (network flows, matching theory), enumeration (permutations and combinations, generating functions, inclusion-exclusion), and extremal combinatorics (pigeonhole principle, Ramsey's theorem). Usually offered every second year.
Staff

MATH 100a Introduction to Algebra, Part I
[ sn ]
Prerequisite: MATH 23b and MATH 15a or 22a, or permission of the instructor. Students may take MATH 28a or 100a for credit, but not both.
An introduction to the basic notions of modern algebra—rings, fields, and linear algebra. Usually offered every spring.
Bong Lian

MATH 100b Introduction to Algebra, Part II
[ sn ]
Prerequisite: MATH 100a or permission of the instructor. Students may take MATH 28b or 100b for credit, but not both.
A continuation of MATH 100a, culminating in Galois theory. Usually offered every second year.
Staff

MATH 108b Introduction to Number Theory
[ sn ]
Prerequisites: MATH 23b and MATH 15a or 22a, or permission of the instructor.
Congruences, finite fields, the Gaussian integers, and other rings of numbers. Quadratic reciprocity. Such topics as quadratic forms or elliptic curves will be covered as time permits. Usually offered every second year.
Staff

PHIL 106b Mathematical Logic
[ hum sn ]
Covers in detail several of the following proofs: the Gödel Incompleteness Results, Tarski's Undefinability of Truth Theorem, Church's Theorem on the Undecidability of Predicate Logic, and Elementary Recursive Function Theory. Usually offered every year.
Jennifer Marušić

PHYS 29a Electronics Laboratory I
[ sn ]
Prerequisites: PHYS 11a, b or PHYS 15a, b; and PHYS 19a, b or permission of instructor. Students without a background in Physics should contact the instructor to discuss course requirements and receive permission to enroll.
Introductory laboratory in electronics. Topics to be covered are time constants, frequency response, rectification, amplification, radio reception, combinatorial logic, digital state machines, and analog-to-digital conversion. The class will solve first and second order differential equations directly and with the help of the complex exponential. Usually offered every year.
Kevan Hashemi