Build production-level AI systems through gaining four critical skills: (1) Automating model development via newly developed and existing data/model pipelines (2) Selecting, adapting, and optimizing newly developed and existing models for performance and computing resource use via feature selection, model architecture, hyperparameter tuning, metrics introspection, transfer learning, and ensemble creation. (3) Form a complete system through the integration of supporting technologies such as high speed messaging, real-time APIs, distributed/parallel processing, data storage (NoSQL), and system management. (4) Packaging into a deployed system via containerization and orchestration including post-deployment adaptation across heterogeneous computing fabrics (cloud to edge). The student acquires these skills through developing a realistic, hands-on, collaborative, and incremental project that produces optimized models integrated into an operational system deployed across hybrid computing environments.
Course Prerequisite(s)
Working knowledge of Python, and Machine Learning Model development from course EN.705.603.
Course Offerings
|
Open
Production Artificial Intelligence (AI) Systems
01/21/2025 - 04/29/2025
Tues 4:30 p.m. - 7:10 p.m. |