DS 3001: Foundations of Data Science :: D-term 2020

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Tentative Schedule (subject to change)

Class #

Date

Topic

Readings

Homework

Project

1

3/27

Course overview & What is Data Science? Data Collection; Data Exploration

https://en.wikipedia.org/wiki/Data_science, Doing Data Science Chapter 1

Doing Data Science Chapter 2

 

 

2

3/31

Data Exploration & Data Preprocessing

Mining the Social Web chapter 1, DMCT 2

DMCT 3

HW1 out

 

3

4/3

Linear Regression

Ng¡¯s note; Data Science from Scratch: Chapters 14 and 15

 

Form a team by April 3

4

4/7

Linear Regression; Classification

IDM 3

 

 

5

4/10

Classification

 

HW2 out

 

6

4/14

Classification; Visualization

Tufte 1, 2, 4

 

 

7

4/17

Exam1

 

 

 

8

4/21

Visualization; Clustering

MMD 7, DMCT 10

 

 

Project proposal due: April 21

9

4/24

Classification;

PageRank;

IIR 13.1 and 13.2

MMD 5

HW3 out

 

10

4/28

Recommender System; Project Workday

MMD 9;

Item-based Collaborative Filtering Recommendation Algorithms

Matrix Factorization Techniques for Recommender Systems, Netflix Prize, How the Netflix Prize was won

 

 

11

5/1

Recommender

MMD 2

HW4 out

Check Point due: 5/1

12

5/5

Recommender Cloud Computing & MapReduce, Spark

spark-intro,  https://spark.apache.org/docs/2.2.0/rdd-programming-guide.html, https://data-flair.training/blogs/spark-rdd-operations-transformations-actions/

 

 

13

5/8

Exam2

 

 

 

14

5/12

Project Presentation

 

 

Project deliverables due: May 11