Courses

Core Courses

Core coursework is designed for students to develop a foundation in statistical analysis and cultivate technical skills in programming, data mining, machine learning, database management, and data and network security. Students also develop techniques to effectively visualize and then communicate results to stakeholders.

Electives

Students are required to take three elective courses to be completed in their last two terms. The elective coursework allows students to customize more in-depth competencies in a range of data science-related disciplines.

Students may choose a specialization as their elective coursework. Two specializations are offered – Machine Learning or Business Analytics. The specializations are custom curriculum options for students who desire a tailored approach to learning and a thorough understanding of subject matter specific to their academic and career goals. Specializations are available for all students but are not required. Students who do not pursue a specialization have the option to select the electives that best fit their overall goals.

Capstone

On-Campus Immersion

Bridge Courses

To better prepare students for the academic rigor of the Master of Science in Data Science program, there is a self-paced bridge course available — a refresher course in statistics. This self-paced course is designed to help you review statistical knowledge before classes begin.

Credit for Prior Learning

If you’ve completed any data science boot camp, you could be eligible to receive credit toward an online Master of Science in Data Science from SMU. We offer up to six graduate credit hours in total to all students admitted into our online graduate program.

Use your boot camp certificate(s) to potentially save more than $10,000 in graduate tuition. Learn more about our credit for prior learning opportunities here.

All SMU Data Science Boot Camp graduates in good standing are eligible to be considered for Credit for Prior Learning (CPL) for one or both of the following Master of Science in Data Science courses: