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]

Proj1 (due 2/12 @ 6pm)

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]

Lab4 (due 2/13)

HW2 (extended due Wed 2/20 @ 11:59pm)

8 2/14/19

SQL [slides]

5 9 2/19/19

Dimensionality Reduction [slides]

Lab5 (due 2/20)

HW3 (due Mon 2/25 @ 11:59pm)

10 2/21/19

PCA [slides]

6 11 2/26/19

Case Study, Review

Lab6

12 2/28/19

Midterm 1

7 13 3/5/19

Modeling and Estimation

Lab7

Disc7

HW4

14 3/7/19

Gradient Descent for Model Estimation

8 15 3/12/19

Generalization and Empirical Risk Minimization

Lab8

Disc8

HW5

16 3/14/19

Linear Regression and Feature Engineering

9 17 3/19/19

Bias-Variance Tradeoff and Regularization

Lab9

Disc9

HW6

18 3/21/19

Cross-Validation and Regularization

10 19 3/26/19

Spring Break

20 3/28/19

Spring Break

11 21 4/2/19

Classification and Logistic Regression I

Lab10

Disc10

Proj2

22 4/4/19

Classification and Logistic Regression II

12 23 4/9/19

What's Next in Classification

Lab11

Disc11

24 4/11/19

Midterm 2

13 25 4/16/19

Hypothesis Testing I

Lab12

Disc12

Proj3

26 4/18/19

Hypothesis Testing II

14 27 4/23/19

Distributed Computing I

Lab13

Disc13

28 4/25/19

Distributed Computing II

15 29 4/30/19

Case Study, Review

Lab14

Disc14

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)