As a course tutor, I spent 8 hours per week running two 1-hour tutoring sections with 5 students each to focus on exam-level practice problems, guiding students through assignments and conceptual ideas in office hours for 2 hours per week, discussing pedagogical best practices with other tutors and TAs, providing feedback on worksheets, proctoring exams, and grading assignments for hundreds of students.

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