Certificate Requirements
The certificate program provides basic training on skills required for working in growing and popular fields involving data and data analysis. It provides both statistical and computational background while also allowing to focus on specific technologies. A student pursuing this certificate can choose from one of the two tracks, the computational track and the statistical track. Each track consists of three required courses (9 credit hours) plus three additional elective courses (9 credit hours).
Required Courses for the Computational Track:
| CMP SCI 4340 | Introduction to Machine Learning | 3 |
| CMP SCI 4342 | Introduction to Data Mining | 3 |
| Choose one from the following: | 3 | |
| Exploratory Data Analysis with R | ||
| Mathematical Statistics I | ||
Required Courses for the Statistical Track:
| MATH 4200 | Mathematical Statistics I | 3 |
| MATH 4210 | Mathematical Statistics II | 3 |
| Choose one from the following: | 3 | |
| Introduction to Statistical Methods in Learning and Modeling | ||
| Introduction to Machine Learning | ||
Electives for both tracks:
| Select additional three courses from the following: | 9 | |
| Introduction to Intelligent Web | ||
| Introduction to Artificial Intelligence | ||
| Introduction to Evolutionary Computation | ||
| Introduction to Machine Learning | ||
| Introduction to Data Mining | ||
| Introduction to Biological Data Science | ||
| Introduction to Deep Learning | ||
| Exploratory Data Analysis with R | ||
| Introduction to High-dimensional Data Analysis | ||
| Mathematical Statistics I | ||
| Mathematical Statistics II | ||
| Bayesian Statistical Methods | ||
| Introduction to Statistical Computing | ||
| Introduction to Statistical Methods in Learning and Modeling | ||
| Introduction to Stochastic Processes | ||
Residency requirement: of the required six courses at least five must be taken at the University of Missouri – St. Louis. Elective courses may be substituted with the permission of the program director. For more information, contact the department chair or email info@arch.umsl.edu.
Learning Outcomes
Upon completion of a Certificate in Data Science at the University of Missouri St. Louis, students will be able to:
- Identify, interpret, and manage the computational issues involved in the handling of large volumes of data
- Apply algorithmic principles and statistical theories to analyze data-sets
- Build and evaluate data-based models
- Apply machine learning techniques to data-mining problems