Post-Baccalaureate Certificate in Computational Artificial Intelligence and Machine Learning
Certificate Level: Graduate
Admission Requirements: Bachelor's degree
Certificate Type: Post-Baccalaureate
Number of Credits to Completion: 12.0
Instructional Delivery: Online
Calendar Type: Quarter
Expected Time to Completion: 1 year
Financial Aid Eligibility: Not aid eligible
Classification of Instructional Program (CIP) Code: 11.0701
Standard Occupational Classification (SOC) Code: 15-0000
About the Program
The Post-Baccalaureate Certificate in Computational Artificial Intelligence and Machine Learning accepts applicants who hold Bachelor degrees in Computer Science, or have completed a Post-Baccalaureate Certificate in Computer Science Foundations, and offers them opportunities to learn the computational elements of artificial intelligence and machine learning. The aim is to provide a strong foundation in this emerging area, with a focus on mathematical fundamentals, algorithms and real-world applications.
Admission Requirements
Please visit the School of Computer and Information Sciences website to learn more about admission requirements.
Additional Information
For more information about this program, please visit the School of Computer and Information Sciences website.
Program Requirements
| Required Courses | ||
| CS 510 | Introduction to Artificial Intelligence | 3.0 |
| CS 613 | Machine Learning | 3.0 |
| CS 615 | Deep Learning | 3.0 |
| Elective Course | 3.0 | |
| Select one course from the following: | ||
| Data Structures and Algorithms I | ||
| Theory of Computation | ||
| Introduction to Computer Vision | ||
| Responsible Machine Learning | ||
| Advanced Artificial Intelligence | ||
| Game Artificial Intelligence | ||
| Applications of Machine Learning | ||
| Robust Deep Learning | ||
| Algorithmic Game Theory | ||
| Cognitive Systems | ||
| Natural Language Processing with Deep Learning | ||
| Applied Artificial Intelligence | ||
| Total Credits | 12.0 | |
Sample Plan of Study
| First Year | ||
|---|---|---|
| Fall | Credits | |
| CS 510 | Introduction to Artificial Intelligence | 3.0 |
| Credits | 3 | |
| Winter | ||
| Elective Course | 3.0 | |
| Credits | 3 | |
| Spring | ||
| CS 613 | Machine Learning | 3.0 |
| Credits | 3 | |
| Summer | ||
| CS 615 | Deep Learning | 3.0 |
| Credits | 3 | |
| Total Credits | 12 | |