Brandeis International Business School

Programs > MSBA > Curriculum

Core Curriculum

Solve Real-world Problems

students presenting at three day startup competition

The Master of Science in Business Analytics equips students to analyze data. 

Key Elements

  • Learn data management and pre-processing, management-oriented visualization, data structures and analysis, selected machine learning methods, and predictive modeling.
  • Build models and execute analyses to address current needs of businesses as well as solve problems presented in cases.
  • Focus on solving real-world problems as well as gaining experience with current, widely adopted software tools.
“My job is technical, and I couldn’t do it without the data science tools and techniques I picked up throughout the MSBA program.”

Mduduzi Langwenya, MSBA’19 Mduduzi Langwenya, MSBA’19, Manager, Data Scientist at Takeda

Curriculum and Timeline

The MSBA program is 12-months or 16-months in length and requires 41 credits. The MSBA program requires 29 core credits. Practicum options will vary for students based on the term in which they begin the program. Students have the opportunity to take courses at other institutions in the area in related fields.

Program Requirements

Core Requirements (21 credits)

  • BUS 224g: Launching Your Global Career (1 credit)
  • BUS 215f: Python and Applications to Business Analytics (2 credits)
  • BUS 211a: Foundations of Data Analytics (4 credits)
  • BUS 212a: Advanced Data Analytics (4 credits)
  • BUS 240f: Information Visualization (2 credits)
  • BUS/FIN 241a: Machine Learning and Data Analysis for Business and Finance (4 credits)
  • ECON 213a: Applied Econometrics with R (4 credits)

Group 1 Electives (4 credits required)

  • BUS 256a: Marketing Analytics (4 credits)
  • ECON/FIN 250a: Forecasting in Finance and Economics (4 credits)
  • BUS 276a: Business Dynamics (4 credits)

Group 2 Electives (6 credits required)

  • BUS 216f: Python and Applications to Business Analytics II (2 credits)
  • BUS 233a: Entrepreneurship and Rapid Prototyping (4 credits)
  • BUS 252a: Marketing Management (4 credits)
  • BUS 253a: Marketing Research (4 credits)
  • BUS 254a: Branding Strategy (4 Credits)
  • BUS 257f: Social Media and Advertising (2 credits)
  • BUS 259f: Digital Marketing (2 credits)
  • BUS 260a: Competition and Strategy (4 credits)
  • BUS 261a: Managing Technology and Innovation (4 credits)
  • BUS 272a: Operations Management (4 credits)
  • BUS 274f: Supply Chain Analytics (2 Credits)
  • BUS 243f: Introduction to Natural Language Processing (2 credits)
  • ECON/FIN 243a: Technological Rivalry
  • RPJM 101: Foundations of Project Management (3 credits)
  • FIN 201a: Investments (4 credits)
  • FIN 203a: Financial Management (4 Credits)
  • FIN 217f: Corporate Financial Modeling (2 credits)
  • FIN 218f: Portfolio Financial Modeling (2 credits)
  • FIN 234a: Social Impact Investing
  • FIN 270a: Options and Derivatives (4 credits)
  • FIN 282f: From Cyber to Covid: Shocks, Risks, and Opportunities in Finance (2 credits)
  • FIN 285a: Computer Simulations and Risk Assessment (4 credits)
  • HS 256f: Healthcare Analytics and Data Mining
  • HS 340f: Advanced Topics in Healthcare Analytics and Data Mining

May include any course from Group 1.

Group 3 Electives (6 credits required)

  • BUS 297a: Internship (2 credits) or any FIN, BUS (except BUS 249f), ECON, BUS/FIN or ECON/FIN course offered at International Business School (including, but not limited to the courses listed above, if not used to fulfill another requirement)

Capstone (4 credits required)

  • BUS 286a: Applications of System Dynamics (4 credits)
  • BUS 290a: Directed Research (4 credits)
  • BUS 294a: Field Project in Data Analytics (4 credits)
  • BUS 296a: Internship (4 credits)
Sample Fall Course Plan: 12-Month

Fall (17 credits)

  • BUS 211a: Foundations of Data Analytics (4 credits)
  • BUS 240f: Information Visualization (2 credits)
  • ECON 213a: Applied Econometrics with R (4 credits)
  • BUS 215f: Python and its Application to Business Analytics (2 credits)
  • BUS 224g: Launching Your Global Career (1 credit)
  • Electives (4 credits)

Spring (18 credits)

  • BUS 212a: Advanced Data Analytics (4 credits)
  • BUS/FIN 241a: Machine Learning and Data Analysis for Business and Finance (4 credits)
  • Electives (10 credits)

Summer (6 credits)

Electives (2 credits)

Capstone (4 credits):

  • Internship
  • Field Project
  • Directed Research
Sample Fall Course Plan: 16-Month

Fall (13 credits)

  • BUS 211a: Foundations of Data Analytics (4 credits)
  • BUS 240f: Information Visualization (2 credits)
  • BUS 215f: Python and its Application to Business Analytics (2 credits)
  • ECON 213a: Applied Econometrics with R (4 credits)
  • BUS 224g: Launching Your Global Career (1 credit)

Spring (16 credits)

  • BUS 212a: Advanced Data Analytics (4 credits)
  • BUS/FIN 241a: Machine Learning and Data Analytics for Business and Finance (4 credits)
  • Electives (8 credits)

Summer (4 credits)

Capstone:

  • Internship
  • Field Project
  • Directed Research

Fall (Remaining credits)

  • Electives (Remaining credits, minimum 4)