BZAN7716

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
2

Requirements fulfilled

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

Official evaluation summary

3.72 / 5

Based on 349 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

  • Jiri Chod
    Fall 2026, Midterm Fall 2025, Midterm Fall 2023, Midterm Fall 2022, 2024FALL1 · Official rating 3.95/5
  • Pieter Vanderwerf
    Midterm Fall 2021 · Official rating 4.20/5

Sections

  • Section 01
    Fall 2026 · Jiri Chod · Fulton Hall 150 MW 01:45PM-03:45PM · Offered
  • Section 02
    Fall 2026 · Jiri Chod · Fulton Hall 150 MW 11:00AM-01:00PM · Offered