Schedule

Here’s your roadmap for the course

  • Content (): This contains the readings, slides, data files, etc. for each session. These will also be added on Canvas on the day of each session. It helps to read the material before each session.
  • Example (): This page contains worked examples of fully annotated R code that you can use as a reference. This is only a reference page—you don’t have to necessarily do anything here.
  • Exercise (): These are interactive exercises where you have to provide R code in your browser to solve a problem, much like Datacamp. These are not graded, but are always there for your reference.
  • Assignment (): This page contains instructions for the three workshop exercises (3-4 brief tasks plus a challenge), for the individual portfolio website project, and the final group project. Assignments are due by 11:59 PM UTC on the day they’re listed.
Foundations: EDA and Intro to Data Science Content Example Exercise Assignment
1 09 Mar Lecture 1: Exploratory Data Analysis
2 09 Mar Workshop 1: Import, visualise, and manipulate data
14 Mar Homework 1 Due
Inferential Statistics Content Example Exercise Assignment
3 15 Mar Lecture 2: Sampling and Probability Distributions
4 15 Mar Workshop 2: Confidence Intervals; reshape data
21 Mar Homework 2 Due
5 22 Mar Lecture 3: Hypothesis Testing; there is only one test
6 22 Mar Workshop 3: Hypothesis testing; A/B testing; simulating with infer
29 Mar Homework 3 Due
Regression Models Content Example Exercise Assignment
7 30 Mar Lecture 4: Introduction to regression models
8 30 Mar Workshop 4: Workshop on regression
9 06 Apr Workshop 5: Multiple regression
11 Apr Final project due
10 12 Apr Group presentations and course warp-up
12 Apr Portfolio website due
19 Apr Final Exam