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Master's in Data Science Courses

The courses are designed and taught by our faculty, who are industry experts and practice-oriented. The courses teach skills for the workplace. The degree can be tailored for your professional needs with your choice of management electives on top of a core curriculum.

Focus Areas covered by the degree include:

  • Data Science Foundation
  • Machine Learning in Finance
  • Programming, Optimization and Computing
  • Quantitative Finance
  • Foundational Finance

The program offers students a wide range of management electives from business disciplines that provide decision making analytics in context of a business framework. These courses will provide:

  • Broad foundations of business by taking courses such as Marketing, Organization Behavior, Operations, and Strategy
  • Depth in functional areas in business by taking courses like Marketing Analytics and Supply Chain Analytics
  • Business skills in Change Management and Negotiation

The table below summarizes the master's degree requirements. Once you are admitted to the program, you will work with your advisor on the best electives based on your professional goals as well as the sequence of courses. It is recommended that you complete both core courses before taking an elective course.

The plan of study of the 30 credit degree is provided below:

Plan of Study by Focus Area Area Credit
Data Science Foundation 6
Machine Learning in Finance 6
Programming, Optimization and Computing 4
Quantitative Finance 3
Foundational Finance 3
Seminar 1
Management Electives 7
Grand Total 30

A typical degree plan of study for the Master’s Degree in Data Science in Finance is shown below.

Course descriptions are provided here (PDF).

Focus Area Course Title Credits
Data Science Foundation Probability 2
Data Science Foundation Applied Statistics 2
Data Science Foundation Statistical Inference 2
Machine Learning in Finance Machine Learning in Finance 1 3
Machine Learning in Finance Machine Learning in Finance 2 3
Programming, Optimization and Computing Data Engineering I 1
Programming, Optimization and Computing Data Engineering II 1
Programming, Optimization and Computing Foundations of Decision Making 1
Programming, Optimization and Computing Numerical Computing for Data Science 1
Quantitative Finance Quantitative Finance 1 3
Foundational Finance Financial Management 3
Seminar Data Science in Finance Seminar 1
Management Electives See Management Electives 7

 

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Phone: 765-496-0990

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