About the Degree
The Michigan Tech Advantage
Our degree will provide you with a broad-based education in data mining, predictive analytics, cloud computing, data-science fundamentals, communication, and business acumen. Additionally, you will gain a competitive edge through domain-specific specialization in disciplines of science and engineering. You will have the freedom to explore and develop your own interests in one or more domains.
Prerequisites
Entry into this program assumes basic knowledge in statistical and mathematical techniques, computer programming, information systems and databases, and communications, obtained through a degree in business, science, or an engineering discipline.
Course Work Degree
Our Master of Science in Data Science is a terminal degree designed to prepare students for careers in industry and government.
Core Courses—12 credits
The four required core 3-credit courses focus on fundamental skills in data science analytics, data mining, and business analytics. These courses are:
- UN 5550—Introduction to Data Science (Fall, 3 credits)
- MA 5790—Predictive Modeling (Fall, 3 credits)
- CS 4821/MA 4795—Data Mining (Spring, 3 credits)
- BA 5200—Information Systems Management and Data Analytics (Fall, 3 credits)
Foundational Courses—Maximum of 6 credits
A maximum of six credit hours of foundational skills courses at the 3000–4000 level may be applied to the Master of Science in Data Science. These courses will build skills necessary for successful completion of the MS in Data Science. Some students will not need to take these foundational courses and will instead use the domain electives to reach the credit requirements of this program.
The 2000-level courses listed here cannot be counted towards the requirement for the MS in Data Science but may be necessary for a given student to build their foundational knowledge.
- MA 2330—Introduction to Linear Algebra (3 credits)
- MA 3710—Engineering Statistics (3 credits)
- MA 3715—Biostatistics (3 credits)
- MA 3740—Statistical Programming and Analysis (3 credits))
- MIS 2000—IS/IT Management (3 credits)
- MIS 2100—Introduction to Business Programming (3 credits)
- MIS 3100—Business Database Management (3 credits)
- MKT 3600—Marketing Research (3 credits)
- CS 2321—Data Structures (3 credits)
- CS 3425—Database (3 credits)
- SAT 3002—Application Programming Introduction (3 credits)
- SAT 3210—DB Management (3 credits)
- SAT 4600—Web Application Development (3 credits)
Electives—Minimum of 6 credits
At least 6 credits must be taken from the list of approved 3-credit Data Science elective courses below:
- CS 5841/EE 5841—Machine Learning (3 credits)
- CS 5471—Advanced Topics in Computer Security (3 credits)
- MA 5781—Time Series Analysis and Forecasting (3 credits)
- BA 5740—Managing Innovation & Technology (3 credits)
- PSY 5210—Advanced Statistical Analysis and Design I (4 credits)
- FW 5083—Bioinformatics Programming and Skills (3 credits)
- PH 4395—Computer Simulation in Physics (3 credits)
- UN 5390—Scientific Computing I (3 credits)