Seize the opportunity and go places.
The MS in Business Analytics is a 41-credit program that develops your ability to think critically about data problems in business contexts. The curriculum is primarily designed to enhance your statistical and programming acumen through rigorous hands-on coursework. Along the way, you’ll also learn the essential soft skills that are highly valued by employers, ranging from elective communication to collaboration and leadership. Moreover, as data-driven decision making becomes ever more embedded in corporate life, you’ll be prepared to think about the ethical and legal challenges that come with collecting, storing, managing, and using data. Ultimately, you will gain a combination of technical and interpersonal skills to enable holistic data-driven decision making.
Beginning in mid-July, the program will intensively cover core concepts in programming and data analysis. This semester will also include additional lab time. From there, you’ll enter the fall semester, where you’ll fortify your understanding of causal, predictive, and unsupervised models through more advanced statistics and machine learning. In the spring, you’ll apply this knowledge to a variety of business areas, all leading up to a comprehensive capstone project.
MS in Business Analytics: Curriculum
3 courses | 12 Credits
These courses will intensively cover the fundamentals of programming and data analysis. You’ll learn the importance of data-driven business decision-making, summary statistics, data architecture, data cleaning, and more in your three summer courses.
Basic Quant Methods
- Importance of data-driven business decision-making, summary stats, regression, probability, Excel
Programming 1 (R or Python plus tools)
- Programming, IDEs/Source control/Tools, Choosing analytics tools, Data Architecture
Data and Databases
- SQL, NoSQL, Data cleaning, data architectures
4 courses | 12 credits
These four courses will build upon your knowledge of programming from the summer, as well as touching on important concepts like data cleaning and munging, advanced regression, text and data mining, and supervised/predictive methods.
- Combining programming and databases, data cleaning and munging, visualization
- Advanced Regression, Instrumental variables, diff-in-diff
- Supervised/Predictive Methods (ML)
- Unsupervised Methods (ML); Text and data mining
1 course | 3 credits
Your winter intensive course will consider both data in business and the legal and ethical considerations of business.
Data in Business
- Data in Business, Legal and Ethical considerations
4 courses | 12 credits
These courses will focus on the challenges businesses face in the following areas. You will use skills learned in the Fall semester to work on problem sets within the business context. The classes will be built around problem sets and/or projects. Another important component of this semester will be the capstone project which will use curated real-world problems/data.
- Topics in Marketing Analytics
- Topics in Operations and Supply Chain Analytics
- Topics in FE/AC Analytics
- Topics in HR Analytics
Ongoing Courses (Fall & Spring)
Throughout your time in the program, you will learn valuable soft skills in the following areas of business leadership.
- Career Management
More than a degree
Upon completion of the MS in Business Analytics program, you will:
- Be able to think critically about and frame data problems in a variety of business contexts and apply appropriate analytical methods to find solutions that achieve stated objectives.
- Consider opportunities, needs and constraints of data analytics within the business functions and the strategic importance of decisions made using data.
- Demonstrate critical thinking skills, connecting quantitative and qualitative tools, concepts and context to effectively solve problems and make decisions.
- Demonstrate proficiency with a variety of data-analytic tools.
- Communicate technical information to both technical and non-technical audiences in speech, in writing, and graphically.
- Demonstrate interpersonal, team, collaborative and leadership skills.
- Demonstrate ethical reasoning skills and understand professional responsibilities.