Technology and AI Product Engineering

MSDS 436-DL 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: (1) MSDS 420-DL Database Systems or CIS 417 Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.

Students benefit by taking the Go Learning Studio, MSDS 431-DL Go and AI-Assisted Programming, and MSDS 432-DL Foundations of Data and AI Engineering prior to taking this course.

This course is aligned with both the Data Engineering and Technology Entrepreneurship specializations.

Go to the main page for Data Engineering.

Go to the main page for Technology Entrepreneurship.