Undergraduate Certificate in Data Science

The Data Science Undergraduate Certificate provides students with essential skills necessary to succeed as a data scientist. A data scientist must be able to:

1. Program in a language popular in data science,
2. Extract, manipulate, and visualize data,
3. Apply probability and statistics to quantify uncertainty,
4. Build complex models for finding patterns and explaining data.

Additional training related to database management, high performance computing, and modeling is necessary for advanced data science analysis. The Data Science Essentials certificate requires students to pass one course related to each of the following competencies: programming, probability and statistics, data manipulation and visualization, and data modeling.

Learning Outcomes:

• Outcome 1: Students can competently program in a language popular in data science.
• Outcome 2: Students can extract, manipulate, and visualize data.
• Outcome 3: Students can apply probability and statistics to quantify uncertainty.
• Outcome 4: Students can build complex models for finding patterns and explaining data.

Course Requirements:

Programming -- In order to ensure adequate programming skills for data science, students should take a course that develops strong programming skills in a programming language popular in data science (e.g., Python, R, Julia). The list of currently approved courses includes:

• MATH 1376 -- Programming for Data Science
• MATH 4650 -- Numerical Analysis I
• ISMG 4400 -- Web Application Development (Programming Fundamentals with Python)
• CSCI 1410 -- Fundamentals of Computing and CSCI 1411 -- Fundamentals of Computing Laboratory

Probability and statistics -- In order to ensure that students can accurately quantify the likelihood of various outcomes and quantify uncertainty related to estimation and prediction, students should take a course that covers basic probability and statistics. The list of currently approved courses includes:

• MATH 2830 -- Introductory Statistics (or equivalent coursework with approval by the Director of Data Science)
• MATH 3382 -- Statistical Theory
• MATH 3800 -- Probability and Statistics for Engineers

Data manipulation and visualization -- In order to ensure that students are able to comfortably work with and visualize data, students should take a course developing skills related to obtaining, manipulating, and visualizing data. The list of currently approved courses includes:

• MATH 3376 -- Data Wrangling & Visualization

Data modeling -- In order to ensure that students are able to build reasonably complex models for explaining or identifying patterns in data, students should take a course that largely focuses on describing the behavior of data (whether synthetic or observed) via tools like simulation, direct model building, association, or a complementary approach. The list of currently approved courses includes:

• MATH 3301 -- Introduction to Optimization in Operations Research
• MATH 4387 -- Applied Regression Analysis
• MATH 4830 -- Applied Statistics