Artificial Intelligence Software Testing and ML/Ops
| Course Code | COMP-315 |
|---|---|
| Lecture hours per week | 2 |
| Lab hours per week | 2 |
| Course Availability | Open |
| Description | During the first half of this course, students will have opportunity to explore techniques for ensuring reliability, accuracy, and robustness in AI-driven applications. Students will also learn advanced testing methodologies, including automated, performance, and ethical testing, to maintain high software quality in AI systems, with practical labs emphasizing real-world tools for AI model validation and software assurance. In the second half of the course, students will learn about ML/Ops and LLM/Ops. Students will learn best practices in model lifecycle management, automation, monitoring, designing feedback loops and collaboration between data science and operations teams. Students will also have opportunity for hands-on labs that provide practical experience with most common ML/Ops and LLM/Ops tools and practices for building reliable, scalable AI systems. |