The Machine Learning and Data Science option in Computer Engineering prepares students for a career in computer engineering with an emphasis on machine learning and data science. The purpose of this option is to provide guidance and recognition for students pursuing this career path. The option uses 19 of the elective credits within the 120-credit Computer Engineering BS degree program to focus on the mathematics, tools, and practices associated with machine learning and data science in engineering. Students selecting this option must submit an option declaration form to the dean’s office in Engineering Hall.
Requirements
Machine Learning and Data Science Required Courses
| Code | Title | Credits |
|---|---|---|
| E C E 204 | Data Science & Engineering 1 | 3 |
| E C E 331 | Introduction to Random Signal Analysis and Statistics (typically offered fall) 2 | 3 |
| E C E/COMP SCI/M E 532 | Matrix Methods in Machine Learning 1 | 3 |
| E C E/COMP SCI/M E 539 | Introduction to Artificial Neural Networks 3 | 3 |
| COMP SCI 564 | Database Management Systems: Design and Implementation 4 | 4 |
| Total Credits | 16 | |
- 1
This course can be taken as a Professional Elective.
- 2
This course fulfills the Probability requirement.
- 3
This course can be taken as a CMPE Elective II.
- 4
This course fulfills the System Software Requirement.
Machine Learning and Data Science Elective
| Code | Title | Credits |
|---|---|---|
| Choose one as an Advanced, Professional, or Free Elective: | 3-4 | |
| Digital Signal Processing (typically offered fall) 1 | ||
| Introduction to Optimization 1 | ||
| Image Processing (typically offered fall) 1 | ||
| Probability and Information Theory in Machine Learning (typically offered fall) | ||
| Ethics of Data for Engineers | ||
| Linear Optimization 1 | ||
| Introduction to Artificial Intelligence | ||
| Medical Image Analysis 1 | ||
| Introduction to Bioinformatics | ||
| Introduction to Algorithms | ||
| Fundamentals of Industrial Data Analytics | ||
| Machine Learning in Action for Industrial Engineers | ||
| Data and Algorithms: Ethics and Policy | ||
| Introduction to Stochastic Processes 1 | ||
| An Introduction to Brownian Motion and Stochastic Calculus 1 | ||
| Introduction to Computational Materials Science and Engineering 1 | ||
| Applied Categorical Data Analysis 1 | ||
| Statistical Experimental Design 1 | ||
| Applied Multivariate Analysis 1 | ||
| Financial Statistics 1 | ||
- 1
This course has additional requisites not required for the BS in Computer Engineering.