Syllabus
The materials for each lecture are linked in the table below. Alternatively, you can browse:
 The Google Drive folder containing all lecture slides.
 The YouTube playlist of all recorded screencasts.
Week  Lecture  Date  Topic  Lab  Discussion  Homework 

1  1  06/24/2019 
Introduction to Data Science, Logistics, Study Design [slides]



2  06/25/2019 
Data Tables with pandas Part 1 [slides]



3  06/26/2019 
Data Tables with pandas Part 2 [slides]


4  06/27/2019 
Data Cleaning [slides]




2  5  07/01/2019 
Visualization [slides]


6  07/02/2019 
Visualization [slides]

Lab3 (due 07/02 @ 11:59PM) 

7  07/03/2019 
EDA & Working with Text [slides]

HW2 (due 07/09 @ 11:59PM) 

8  07/04/2019 
Holiday (no class)

HW3 (due 07/12 @ 11:59PM) 

3  9  07/08/2019 
SQL [slides]


10  07/09/2019 
Dimensionality Reduction [slides]

Lab5 (due 07/09 @ 11:59PM) 

11  07/10/2019 
PCA [slides]


12  07/11/2019 
Midterm Review (originally a Case Study) [slides]

Lab6 (due 07/11 @ 11:59PM) 

4  13  07/15/2019 
Midterm Review [slides]


14  07/16/2019 
Midterm


15  07/17/2019 
Foundations of Statistical Inference: Random Variables and Estimators [slides]

HW4 (due 07/23 @ 11:59PM) 

16  07/18/2019 
Foundations of Statistical Inference: Risk and Loss Functions [slides]


5  17  07/22/2019 
Linear Regression [slides]


18  07/23/2019 
Gradient Descent [slides]

Lab 8 (due 07/23 @ 11:59PM) 
HW5 (due 07/26 @ 11:59PM) 

19  07/24/2019 
Feature Engineering and BiasVariance [slides]


20  07/25/2019 
CrossValidation and Regularization [slides]

Lab 9 (due 07/25 @ 11:59PM) 


6  21  07/29/2019 
Logistic Regression [slides]


22  07/30/2019 
Classifier Evaluation and Fitting [slides]

Lab 10 (due 07/30 @ 11:59PM) 

23  07/31/2019 
Decision Boundaries, Modeling Considerations [slides]



24  08/01/2019 
Inference for Modeling [slides]

Lab 11 (due 08/01 @ 11:59PM) 

7  25  08/05/2019 
Big Data and Ray (Guest Lecturer: Robert Nishihara) [slides]


26  08/06/2019 
Big Data and Spark, Decision Trees [slides]

Lab 12 (due 08/06 @ 11:59PM) 

27  08/07/2019 
Random Forests, Runtime Analysis, Modeling Overview [slides]



28  08/08/2019 
Ethics & Conclusion [slides]


8  29  08/12/2019 
Final Review [slides]


30  08/13/2019 
Final Review [slides]


31  08/14/2019 
Break (no lecture)


32  08/15/2019 
Final (9:30am  12:30pm)
