Syllabus

This syllabus is still under development and is subject to change.

Week Lecture Date Topic Lab Discussion Homework
1 1 1/22/19

Course Overview, Motivating/Defining Data Science, Logistics [slides]

2 1/24/19

Study Design [slides]

2 3 1/29/19

Data Tables with Pandas [slides]

4 1/31/19

Data Cleaning [slides]

3 5 2/5/19

Visualization I [slides]

6 2/7/19

Visualization II [slides]

4 7 2/12/19

EDA & Working with Text [slides]

8 2/14/19

SQL [slides]

5 9 2/19/19

Dimensionality Reduction [slides]

10 2/21/19

PCA [slides]

6 11 2/26/19

Case Study [slides]

12 2/28/19

Midterm 1

7 13 3/5/19

Foundations of Statistical Inference (Slides updated 03/12/2019) [slides]

14 3/7/19

Foundations of Statistical Inference

8 15 3/12/19

Linear Regression and Feature Engineering [slides]

  • HW5 (due 3/19 @ 6pm)
16 3/14/19

Gradient Descent for Risk Optimization (Slides updated 03/19/2019) [slides]

9 17 3/19/19

Risk Optimization and Bias-Variance Trade-Off [slides]

  • HW6 (due 4/2 @ 6pm)
18 3/21/19

Cross-Validation and Regularized Regression

10 19 3/26/19

Spring Break

20 3/28/19

Spring Break

11 21 4/2/19

Logistic Regression [slides]

Proj2 (due 4/16 @ 6pm)

22 4/4/19

Classification [slides]

12 23 4/9/19

Prediction: Classification and Regression [slides]

24 4/11/19

Midterm 2

  • Review Session in Wheeler 150 Wed 4/10 8-10 PM
  • Midterm 2 in Wheeler 150 Thurs 4/11 6:40-8 PM

13 25 4/16/19

Prediction: Classification and Regression [slides]

Final Project

26 4/18/19

Inference about Models [slides]

Proj3 (due 5/2 @ 11:59pm)

14 27 4/23/19

Distributed Computing I

Lab11

Disc11

28 4/25/19

Distributed Computing II

15 29 4/30/19

Case Study, Review

HW7

30 5/2/19

Conclusion

16 31 5/7/19

RRR week

32 5/9/19

RRR week

17 33 5/14/19

34 5/16/19

Final Exam (11:30am-2:30pm)