Technology and AI Product Engineering
This course introduces design principles and best practices for implementing systems for data ingestion, processing, storage, and analytics. Students learn about full-stack development and software alternatives for implementing analytics solutions and technology products. They use machine learning, AI, and agent-based technologies. They evaluate system performance and resource utilization in batch, interactive, and streaming environments. Students run performance benchmarks, comparing alternative software stacks. They practice agile/scrum project management as they develop technology products. Recommended prior courses: MSDS 431-DL Go and AI-Assisted Programming and MSDS 432-DL Foundations of Data and AI Engineering.
Prerequisites & course information
Prerequisite: (1) MSDS 420-DL Database Systems or CIS 417-DL Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435-DL Practical Data Science Using Machine Learning.
Sources
- Course catalogue ↗2026–2027