As an Undergraduate Student Instructor, I spent 12 hours per week running two 2-hour lab sections consisting of approximately 35 students each, answering student questions in 3 hours of office hours, shadowing a course tutor’s tutoring section to provide pedagogical mentorship, and proctoring and grading exams.

My section website contains resources I put together specifically for my lab sections.

For more information, visit the course website.

Course Topics

Coding

• Python and NumPy expressions, data types, arrays, and table manipulations
• Histograms and data visualizations
• Functions and iteration

Statistics

• Probability (calculating chances, Bayes’ theorem)
• Sampling, bootstrapping, A/B testing
• Confidence intervals
• Hypothesis testing
• Determining causality

Inference

• Linear regression, least squares, error metrics
• K-nearest neighbours classification