Brandeis International Business School

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.
“The quantitative classes at Brandeis IBS were instrumental in my hunt for a job in data analytics. Here in the Boston area, you can find many companies that will employ graduates with bright minds and technical skills.”

Begli Nursahedov, IBS ’09, Data Scientist, HubSpot

Program Timelines

12-Month Program

Fall

  • BUS 211f Big Data I (2 Credits)
  • BUS 240f Information Visualization (2 Credits)
  • ECON 213a Applied Econometrics with R (4 Credits)
  • Choose one based on track interest:
    • BUS 256a Marketing Analytics (4 Credits)
    • BUS 276a Business Dynamics (4 Credits)
    • FIN 203a Investments\Corp Fin OR Fin 201a Investments (4 Credits)
  • Group 1 or Group 2 Elective (6 Credits)

Spring

  • BUS 212g Big Data II (4 Credits)
  • BUS 215f Python and its Application to Business Analytics (2 Credits)
  • BUS 241f Machine Learning and Data Analysis for Business and Finance (2 Credits)
  • Electives: (Describe Interest Below) (10 Credits)

Summer

  • Practicum: Internship, Field Project, or Directed Research (4 Credits)
16-Month Program

Fall

  • BUS 211f Big Data I (2 Credits)
  • BUS 240f Information Visualization (2 Credits)
  • ECON 213a Applied Econometrics with R (4 Credits)
  • Choose one based on track interest:
    • BUS 256a Marketing Analytics (4 Credits)
    • BUS 276a Business Dynamics (4 Credits)
    • FIN 203a Investments\Corp Fin OR Fin 201a Investments (4 Credits)
  • Group 1 or Group 2 Elective (2 - 4 Credits)

Spring

  • BUS 212g Big Data II (4 Credits)
  • BUS 215f Python and its Application to Business Analytics (2 Credits)
  • BUS 241f Machine Learning and Data Analytics for Business and Finance (2 Credits)
  • Elective in Track: (Describe Interest Below) (6 - 8 Credits)

Summer

  • Practicum: Internship, Field Project, or Directed Research (4 Credits)

Fall

  • Electives - Remaining credits 

Course Requirements

Our core courses provide the basis for business analytics, and our elective courses offer a grounding in the application of business analytics to marketing, finance or business dynamics.
Required Courses (16 credits)
  • BUS 215f Python and its Application to Business Analytics
  • BUS 211f Big Data I
  • BUS 212a Big Data II
  • BUS 240f Information Visualization
  • BUS 241f Machine Learning and Data Analysis for Business and Finance
  • ECON 213a Applied Econometrics with R
Group 1: Core Courses (4 credits required)
  • BUS 256a Marketing Analytics
  • BUS 276a Business Dynamics
  • ECON/FIN 250a Forecasting in Economics and Finance
Group 2: Electives (8 credits required)
  • BUS 233a Entrepreneurship and Rapid Prototyping
  • BUS 252a Marketing Management
  • BUS 253a Marketing Research
  • BUS 254a Branding Strategy
  • BUS 257f Social Media & Analytics
  • BUS 259f Digital Marketing
  • BUS 260a Competition and Strategy
  • BUS 261a Managing Technology and Innovations
  • BUS 272a Operations Management
  • BUS 274f Supply Chain Analytics
  • RPJM 101 Foundations of Project Management
  • FIN 203a Financial Managements OR Fin 201a Investments
  • FIN 217f Corporate Financial Modeling
  • FIN 218f Portfolio Financial Modeling
  • FIN 270a Options and Derivatives
  • FIN 285a Computer Simulation & Risk Analysis

Or any course from Group 1 not taken to satisfy those requirements

Group 3: Electives (8 credits required) Course Suggestions
  • Any BUS, ECON, or FIN course at the International Business School
  • Other approved courses at Brandeis University
  • Or any course from Group 1 or 2 not taken to satisfy those requirements
Capstone (4 credits)
  • BUS 294a Field Project in Data Analytics (4 credits)
  • BUS 296a Internship (4 credits)
  • BUS 286a Applications of System Dynamics (4 Credits)
  • Directed Research (4 credits)