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MSDS 436 Technology Product Engineering

Course Description #

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 intelligent, knowledge-based systems. They evaluate system performance and resource utilization in batch, interactive, and streaming environments. They create and run performance benchmarks for comparing alternative software stacks. Students work in software engineering teams, practicing agile/scrum project management as they develop new technology products. Recommended prior course: MSDS 430-DL Python for Data Science or MSDS 431-DL Data Engineering with Go. 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.

What is required of students? Students participate in weekly discussion forums and programming assignments. They work in agile/scrum teams in developing a full-stack application.

Course Schedule and Topics #

  • Week 1. Course Overview
  • Week 2. Project Management for Technology Products
  • Week 3. Desktop Development (CPU and GPU)
  • Week 4. Server-Side Development
  • Week 5. Client-Side Development
  • Week 6. Batch Processing
  • Week 7. Stream Processing
  • Week 8. Interactive Processing
  • Week 9. Systems Analysis
  • Week 10. Product Delivery and Demonstration

Go to the home page Learning Go for Data Science.

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