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 | Tue. Jan 10 | Lecture 1 | Course Introduction + What is Data Science? | |||
| Tue. Jan 10 | No Guest Lecture | xx | ||||
| Thu. Jan 12 | No Lab | xx | Paper 1 Posted | |||
| 2 | Tue. Jan 17 | Lecture 2 | Exploratory Data Analysis (EDA) | Assignment 1 Posted | ||
| Tue. Jan 17 | Guest Lecture | No Guest Lecture. Tableau Lab | ||||
| Thu. Jan 19 | Lab 1 | Intro to Python + pandas | ||||
| 3 | Tue. Jan 24 | Lecture 3 | Modeling | Paper 1 Due | ||
| Tues. Jan 25 | Guest Lecture | Getting an industry internship, Menglin Wang | ||||
| Thu. Jan 26 | Lab 2 | EDA with NumPy and Matplotlib | Reflection 1 Posted | |||
| 4 | Tue. Jan 31 | Lecture 4 | Regression I | Assignment 1 Due, Assignment 2 Posted | Paper 2 Posted | |
| Mon. Jan 30 | Guest Lecture | Ken Chau, Data scientist at Public Storage | ||||
| Thu. Feb 2 | Lab 3 | Git + Regression with Scikit Learn | Reflection 1 Due | |||
| 5 | Tue. Feb 7 | Lecture 5 | Communication | |||
| Tues. Feb 8 | Guest Lecture | Ethics in Data Visualization (Steven Coyne) | ||||
| Thu. Feb 9 | Lab 4 | Version Control: Git/Github/Bash | Paper 2 Due | Reflection 2 Posted | ||
| 6 | Tue. Feb 14 | Lecture 6 | Simulation | Assignment 2 Due | ||
| Tue. Feb 14 | Tableau Lab | Revision and More Chart Types | ||||
| Thu. Feb 16 | Lab 5 | Simulation with Scikit learn | Assignment 3 Posted | Paper 3 Posted | Reflection 2 Due | |
| 7 | Tue. Feb 21 | READING WEEK | xx | |||
| Tue. Feb 21 | READING WEEK | xx | ||||
| Thu. Feb 23 | READING WEEK | xx | ||||
| 8 | Tue. Feb 28 | Lecture 7 | Classifiers | |||
| Tues. Mar 1 | Guest Lecture | TBD | ||||
| Thu. Mar 2 | Lab 6 | Classification with Scikit learn | ||||
| 9 | Tue. Mar 7 | Lecture 8 | Classifiers 2 | Assignment 3 Due on March 11th, Assignment 4 Posted | ||
| Tue. Mar 7 | Guest Lecture | TBD | ||||
| Thu. Mar 9 | Lab 7 | Twitter API + Natural Language Processing | Paper 3 Due | Reflection 3 Posted | ||
| 10 | Tue. Mar 14 | Lecture 9 | Evaluating Predictions | |||
| Tues. Mar 15 | Guest Lecture | TBD | ||||
| Thu. Mar 16 | Lab 8 | Prediction Metrics | Reflection 3 Due | |||
| 11 | Tue. Mar 21 | Lecture 10 | Clustering | Paper 4 Posted | ||
| Tue. Mar 21 | Guest Lecture | TBD | ||||
| Thu. Mar 23 | Lab 9 | Clustering | Reflection 4 Posted | |||
| 12 | Tue. Mar 28 | Lecture 11 | Data Science Workflow | Paper 4 Due | ||
| Tues. Mar 29 | Guest Lecture | TBD | ||||
| Thu. Mar 30 | Lab | A4 Work Session | Reflection 4 Due | |||
| 13 | Tue. Apr 4 | Lecture 12 | Final Presentations | |||
| Tue. Apr 4 | Guest Lecture | TBD | ||||
| Thu. Apr 6 | Lab | 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).