BZAN7706

Data Analytics 1: Model Building

Machine Learning, big data, data mining, predictive analytics. These are what the course covers. They consist of the creation and use of mathematical computer models to predict important quantities and events with uncanny accuracy. As one book put it, "Who clicks, who buys, and who dies." The course teaches both the principles and the details of the major methods of making and applying these models to actual business problems. To produce models on the computer, students also learn the R coding language. This is the preferred high-level software for Machine Learning and statistical applications.STEM-designated

Course overview

Department
Business Analytics
School
CSOM
Credits
3

Requirements fulfilled

No source-backed degree requirement is attached to this course yet.

Official evaluation summary

4.12 / 5

Based on 537 aggregate responses from BC Avalanche/Blue evaluations.

Data freshness

Course and evaluation data last updated 2026-07-23. Source details and limitations are documented in Data Sources and Methodology.

Instructors

  • Pieter A VanderWerf
    Fall 2026, Summer 2026
  • Jiri Chod
    Fall 2022, Fall 2021 · Official rating 4.09/5
  • Pieter Vanderwerf
    Spring 2026, Fall 2025, Summer 2025, Spring 2025, Fall 2024, Summer 2024, Spring 2024, Fall 2023, Summer 2023, Spring 2023, Fall 2022, Summer 2022, Spring 2022 · Official rating 4.45/5

Sections

  • Section 01
    Summer 2026 · Pieter A VanderWerf · On-line Asynchronous · Offered
  • Section 01
    Fall 2026 · Pieter A VanderWerf · On-line Asynchronous · Offered
  • Section 02
    Fall 2026 · Pieter A VanderWerf · Fulton Hall 245 W 07:00PM-09:30PM · Offered