Lectures

The course covers the following main topics, with corresponding lecture materials available in the lectures folder in our course repository:

Schedule

• Wednesday, August 28: Lecture 01: Welcome to QTM 151 - Introduction. Please make sure to install the necessary software for the course by following the Course Tutorials: How to Install Anaconda, Jupyter, PostgreSQL, VSCode, and Open a Free Educational Account on GitHub.

• Monday, September 02: Labour Day (no class)

• Wednesday, September 04: Lecture 02: GitHub Review, Introduction to Jupyter Notebooks.

  • Extra lecture: Lecture slides. Video recording.
  • Assignment 01: Problem Set 01

• Monday, September 09: Lecture 03: Variables and Lists. Jupyter Notebook, Lecture Slides.

  • Kahoot Quiz.

• Wednesday, September 11: Lecture 04: Mathematical Operations, Arrays, and Random Numbers. Jupyter Notebook, Lecture Slides

  • Kahoot Quiz
  • Assignment 01 due (5%)
  • Assignment 02: Problem Set 02

• Monday, September 16: Lecture 05: Boolean Variables and If/Else Statements. Jupyter Notebook, Lecture Slides.

  • Kahoot Quiz.

• Wednesday, September 18: Lecture 06: While Loops and For Loops. Jupyter Notebook, Lecture Slides

  • Kahoot Quiz
  • Assignment 02 due (5%)
  • Assignment 03: Problem Set 03

• Monday, September 23: Lecture 07: Applications 1: Simulation Studies. Jupyter Notebook. Lecture Slides.

  • Kahoot Quiz.

• Wednesday, September 25: Lecture 08: Functions and Arguments. Jupyter Notebook. Lecture Slides.

  • Kahoot Quiz.
  • Assignment 03 due (5%)
  • Assignment 04: Problem Set 04

• Monday, September 30: Lecture 09: Global and Local Variables. Jupyter Notebook. Lecture Slides.

  • Kahoot Quiz

• Wednesday, October 02: Lecture 10: Quiz 01: Application 02 - Operations over Multiple Datasets (6%)

  • Assignment 05: Problem Set 05

• Friday, October 04: Assignment 04 due (5%)

• Monday, October 07: Lecture 11: Subsetting Data. Jupyter Notebook. Lecture Slides

• Wednesday, October 09: Lecture 12: Application 03: Linear Models

  • Assignment 05 due (5%)
  • Assignment 06: Problem Set 06

• Monday, October 14: Fall Break (no class)

• Wednesday, October 16: Lecture 13: Creating and Replacing Variables

  • Assignment 06 due (5%)
  • Assignment 07: Problem Set 07

• Monday, October 21: Lecture 14: Quiz 2: Application 4: Random Assignment (6%)

• Wednesday, October 23: Lecture 15: Aggregating Data

  • Assignment 07 due (5%)
  • Assignment 08: Problem Set 08

• Monday, October 28: Lecture 16: Merging Data

• Wednesday, October 30: Lecture 17: Introduction to SQL

  • Assignment 08 due (5%)
  • Assignment 09: Problem Set 09
  • Instructions for the Final Project: Final Project

• Monday, November 04: Lecture 18: Quiz 3: Application 5: Practicing Chaining (6%)

• Wednesday, November 06: Lecture 19: Import SQL Data into Python

  • Assignment 09 due (5%)
  • Assignment 10: Problem Set 10

• Monday, November 11: Lecture 20: Merging Tables in SQL

• Wednesday, November 13: Lecture 21: Time Series Analysis

  • Assignment 10 due (5%)

• Monday, November 18: Lecture 22: Quiz 4: Application 6: Practice SQL Queries (6%)

• Wednesday, November 20: Lecture 23: Pivot Tables

• Monday, November 25: Lecture 24: Quiz 5: Application 8: Time Data, Panel Data, and Plots (6%)

• Wednesday, November 27: Thanksgiving Break (no class)

• Monday, December 02: Lecture 25: Manipulating Text Data

• Wednesday, December 04: Lecture 26: Advanced Plots

• Monday, December 09: Final Project due (20%)

Each lecture folder contains an HTML file or a Jupyter notebook (.ipynb) with code examples and explanations, along with any additional resources or datasets used in the lecture.