MBAn Curriculum

15.003 Analytics Tool (3):
Get familiar with different analytics topics, programming languages, and software tools. (Python, R, Julia/JuMP, Github, etc.)

15.072 Advanced Analytics Edge (6):
Examines how data analytics transforms businesses and industries, using examples and case studies in e-commerce, healthcare, social media, high technology, sports, the internet, and beyond.

15.C57 Optimization Methods (12):
Introduces the principal algorithms for linear, network, discrete, robust, nonlinear, and dynamic optimization. Emphasizes methodology and the underlying mathematical structures.
This subject was previously listed as 15.093/6.7200/IDS.200.

15.095 Machine Learning Under a Modern Optimization Lens (12):
Develops algorithms for central problems in machine learning from a modern optimization perspective.

15.572 Analytics Lab: Action Learning Seminar on Analytics, Machine Learning, and the Digital Economy (9):
Student teams design and deliver a project using analytics, machine learning, large data sets, or other digital innovations to create or transform a business or other organization. Culminates with presenting results to an audience that includes IT experts, entrepreneurs, and executives.

15.681 From Analytics to Action (6):
Develops an appreciation for organizational dynamics and competence in navigating social networks, working in a team, demystifying rewards and incentives, leveraging the crowd, understanding change initiatives, and making sound decisions.

15.776 Intensive Hands-on Deep Learning (6)
Fast-paced introduction to deep learning, the engine behind modern artificial intelligence, with an emphasis on developing a practical understanding of how to build models to solve complex problems involving unstructured data. Rapid introduction to deep neural networks and their training. Emphasis on language models, focused on masked and generative modeling and vision models (using diffusions and transformers). Model adaptation via fine-tuning, RL-based training (eg, RLHF, GRPO, etc.). System design concepts, including retrieval augmented generation and agentic system design.

+ One Optional Unrestricted Elective (0-12 units)

IAP holds great significance for MBAn students as it is a bustling and crucial period. Apart from the required courses, MBAn students are also required to engage in the Analytics Capstone Kick-Off, and Company Pitches and prepare for their Capstone interviews & matching.

15.089 Analytics Capstone Project (24 units spanning IAP, Spring, and Summer):
Practical application of business analytics problems within a real company. Teams of 1-2 students, matched with company projects, visit companies to define the project and scope.

15.287 Communication and Persuasion through Data (3):
Focuses on the strategic and tactical use of data to move others to take (the correct) action. Sharpens communication skills via practice and real-world examples.

15.630 Ethics & Data Privacy​ (3)

15.003 Analytics Tool (3):
Get familiar with different analytics topics, programming languages, and software tools. (Python, R, Julia/JuMP, Github, etc.)

15.089 Analytics Capstone Project (24 units spanning IAP, Spring, and Summer):
Practical application of business analytics problems within a real company. Teams of 1-2 students, matched with company projects, visit companies to define the project and scope. 

+ Analytics Electives (27 minimum units must be taken from the Analytics Core, and students can enroll in up to 48 maximum elective units)

15.089 Analytics Capstone Project (24 units spanning IAP, Spring, and Summer):
Practical application of business analytics problems within a real company. Teams of 1-2 students, matched with company projects, visit companies to define the project and scope.

• The Polls and the US Presidential Election in 2020 ….and 2024 (A. Barnett). Learn more.
• Covid‐19 infection risk on US domestic airlines (A. Barnett). Learn more.
• Redesign national lung transplant allocation system using data analytics. Learn more.
• Building a predictive model to capture risk of developing infection in patients receiving chemotherapy (D. Bertsimas)
• Researching a new algorithm to control user social behavior on a running app, in order to maximize usage/running (V. Farias)
• Improve sales forecasting and optimize shop floor display assortment using RFIC data for Zara (G. Perakis)
• Optical Character Recognition (text in images) for commodity supply chain network in Indonesia (N. Trichakis)
• Optimization of the scheduling and routing of Boston School Buses (D. Bertsimas)
• Predicting crop prices and optimizing network flow for rural farmers of India (K. Zheng)