Certificate in Data Science
The graduate-level Certificate in Data Science is designed for business, science, and engineering students at Michigan Tech who wish to upgrade their qualifications for positions in managing and analyzing data.
Our certificate program emphasizes data analytics from a general perspective; however, the skills you will develop are broadly applicable. Data science is interdisciplinary in nature; therefore, the certificate provides students with strong academic training in data analysis in a range of areas:
- computer science.
- math sciences,
- physical sciences,
- environmental science,
- social sciences, and
- business and commerce.
Additionally, the curriculum integrates studies in essential business acumen, communication, and teamwork skills—all of which are highly valued by industry and government agencies.
Course Work Summary
It is expected that students seeking enrollment in this program will have sufficient foundational skills and aptitude in computer programming, statistical analysis, information systems, and databases. The required foundational skills may have been obtained through formal academic qualifications, work experience, or a combination of the two.
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 4790—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)
Elective Courses—3 credits
The remaining 3 credits for the graduate certificate must be taken from the approved list of 3-credit elective courses that are as part of the Master of Science in Data Science program:
- CS 5841/EE 5841—Machine Learning (3 credits)
- CS 5491—Cloud Computing (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)