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 
BiasVariance Tradeoff and Regularization

Lab9 
Disc9 
HW6 
18  3/21/19 
CrossValidation 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 (11:30am2:30pm)
