Data Science Post-baccalaureate sequence

Program Learning Outcomes

The foundations of the post-baccalaureate program in Data Science are curation, mathematical foundations, computational thinking, statistical thinking, and data modeling.

Students who complete this certificate will learn the data cycle of obtaining, curating, managing, processing, exploring, analyzing, and communicating data. They will:

• Connect abstract mathematics with real-world problems involving data.
• Apply computational and statistical thinking to the acquisition and analysis of data.
• Build statistical models and assess them.
• Become proficient in current statistical, numerical, and visualization software.
• Communicate their analyses in both written and visual formats.

Required courses: 24 credits

• CS 445 - Introduction to Database Systems 4 credit(s)
• MATH 206 - Computational Linear Algebra 4 credit(s)
• MATH 307 - Calculus-Based Statistics 4 credit(s)
• DSCI 340 - Algorithms & Data Structures 4 credit(s)
• DSCI 407 - Statistical Modeling and Regression 4 credit(s)
• DSCI 440 - Machine Learning and Data Mining 4 credit(s)