Below is our course schedule, which may change as the course progresses. Details regarding evaluation due dates can be found below the table.
| Week | Date | Session | Description | Assignment | Perusall | Reflection |
|---|---|---|---|---|---|---|
| 1 | Mon. Jan 10 | Lecture 1 | Course Introduction + What is Data Science? | |||
| Mon. Jan 10 | Guest Lecture 1 | xx | ||||
| Wed. Jan 12 | Lab 1 | xx | Paper 1 Posted | |||
| 2 | Mon. Jan 17 | Lecture 2 | Exploratory Data Analysis (EDA) | Assignment 1 Posted | ||
| Mon. Jan 17 | Guest Lecture 2 | Life as a Data Scientist, Aaron Sonabend (Google) | ||||
| Wed. Jan 19 | Lab 2 | Intro to Python + pandas | ||||
| 3 | Mon. Jan 24 | Lecture 3 | Modeling | Paper 1 Due | ||
| Tues. Jan 25 | Guest Lecture 3 | Life as a Data Scientist, Stefanie Nickels (Verily) | ||||
| Wed. Jan 26 | Lab 3 | EDA with NumPy and Matplotlib | Reflection 1 Posted | |||
| 4 | Mon. Jan 31 | Lecture 4 | Regression I | Assignment 1 Due, Assignment 2 Posted | Paper 2 Posted | |
| Mon. Jan 31 | Guest Lecture 4 | Life as a Data Scientist, Kathy Evans (NBA) | ||||
| Wed. Feb 2 | Lab 4 | Git + Regression with Scikit Learn | Reflection 1 Due | |||
| 5 | Mon. Feb 7 | Lecture 5 | Communication | |||
| Tues. Feb 8 | Guest Lecture 5 | Life as a Grad Student, Yanbo Tang, Robert Zimmerman, Siyue Yang (DoSS) | ||||
| Wed. Feb 9 | Lab 5 | Version Control: Git/Github/Bash | Paper 2 Due | Reflection 2 Posted | ||
| 6 | Mon. Feb 14 | Lecture 6 | Simulation | Assignment 2 Due | ||
| Mon. Feb 14 | Guest Lecture 6 | Being an Effective Data Scientist, Paul Varghese (Verily) | ||||
| Wed. Feb 16 | Lab 6 | Simulation with Scikit learn | Assignment 3 Posted | Paper 3 Posted | Reflection 2 Due | |
| 7 | Mon. Feb 21 | READING WEEK | xx | |||
| Mon. Feb 21 | READING WEEK | xx | ||||
| Wed. Feb 23 | READING WEEK | xx | ||||
| 8 | Mon. Feb 28 | Lecture 7 | Classifiers | |||
| Tues. Mar 1 | Guest Lecture 7 | Genomic Data Science, Lisa Strug (U of T) | ||||
| Wed. Mar 2 | Lab 7 | Classification with Scikit learn | Paper 3 Due | |||
| 9 | Mon. Mar 7 | Lecture 8 | Classifiers 2 | Assignment 3 Due, Assignment 4 Posted | ||
| Mon. Mar 7 | Guest Lecture 8 | Natural Language Processing, Alistair Johnson (Sick Kids) | ||||
| Wed. Mar 9 | Lab 8 | Twitter API + Natural Language Processing | Reflection 3 Posted | |||
| 10 | Mon. Mar 14 | Lecture 9 | Evaluating Predictions | |||
| Tues. Mar 15 | Guest Lecture 9 | Life as Data Scientist, Ellen Stephenson (U of T) | ||||
| Wed. Mar 16 | Lab 9 | Prediction Metrics | Reflection 3 Due | |||
| 11 | Mon. Mar 21 | Lecture 10 | Clustering | Paper 4 Posted | ||
| Mon. Mar 21 | Guest Lecture 10 | Life as Data Scientist, Amy Braverman (NASA/JPL) | ||||
| Wed. Mar 23 | Lab 10 | Clustering | Reflection 4 Posted | |||
| 12 | Mon. Mar 28 | Lecture 11 | Data Science Workflow | Paper 4 Due | ||
| Tues. Mar 29 | Guest Lecture 11 | Applications of Hidden Markov Models, Sofia Ruiz (National University of Rosario) and Yunyi Shen (U Wisconsin-Madison) | ||||
| Wed. Mar 30 | Lab 11 | A4 Work Session | Reflection 4 Due | |||
| 13 | Mon. Apr 4 | Lecture 12 | Final Presentations | |||
| Mon. Apr 4 | Guest Lecture 12 | A Statistical Perspective of Data Science, Radu Craiu (U of T) | ||||
| Wed. Apr 6 | Lab 12 | Final Presentations | Assignment 4 Due (4/8) |
Assignments and reflection quizzes are to be submitted via Quercus. Perusall papers are completed within the Perusall application.
The deadline for submission for assignments, Perusall papers, and reflection quizzes is always 10:59am EST on the due date (1 hour before class starts).