whitemt/dat_sf_14

DAT_SF_14

Course materials for General Assembly's Data Science course in San Francisco (4/28/15 - 7/9/15).

Instructor:

• Yuchen Zhao

Experts-in-Residence:

• Alex Chao (Office Hours: 2-6 pm Sundays)

• David Feldman (Office Hours: 4-6:30 pm Tuesdays,Thursdays)

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Course Schedule (Tentative)

Week	Tuesday	Thursday
1	4/28: Introduction to Data Exploration	4/30: Introduction to Machine Learning
2	5/05: Data Format, Access & Transformation	5/07: K-Nearest Neighbors Classification Final Project Kickoff
3	5/12: Naive Bayes Classification HW1 Due	5/14: Regression and Regularization
4	5/19: Logistic Regression HW2 Due	5/21: K-Means Clustering Project Milestone (PM1): Elevator Pitch
5	5/26: Clustering & Decision Trees	5/28: Tree-based Classifiers
6	6/02: Ensemble Techniques Project Milestone (PM2): Data Ready	6/04: Support Vector Machines
7	6/09: Dimensionality Reduction HW3 Due	6/11: Imbalanced Classes and Evaluation Metrics
8	6/16: Recommendation Systems Project Milestone (PM3): First Draft Due	6/18: Natural Language Processing
9	6/23: Final Project Work Session & Peer Feedback Project Milestone (PM4): Peer Feedback Due	6/25: Map-Reduce & Hadoop
10	6/30: Distributed Data Processing (Spark)	7/02: Network Analysis
11	7/07: Project Presentations Day 1 Project Milestone (PM5): Presentation	7/09: Project Presentations Day 2 Project Milestone (PM5): Presentation & Paper

Homework Schedule

HW	Topics	Dataset	Assigned	Due
1	Data Exploration	titanic	5/05	5/12
2	KNN & Cross Validation	iris	5/07	5/19
PM1	Elevator Pitch	project	-	5/21
PM2	Data Ready	project	-	6/02
3	Decision Trees	bank	6/02	6/09
PM3	First Draft Due	project	-	6/16 (Before Class)

Resources

Working in the terminal

• Data Science at the Command Line
• Learning Bash Scripting For Beginners
• Advanced Bash Scripting Guide

Statistical Learning Theory

• Elements of Statistical Learning

Algorithms

• Top 10 Data Mining Algorithms in Plain English

Python

• Data Science from Scratch