README.md

Data Science Course: Lectures and Materials

For the Spring 2014 Data Science course at General Assembly, NYC

Issues: For questions, answers and discussions:

• Closed and Open Issue List (via pulse)
• Create a new issue

Class Meetings

Introduction to Data Science

Monday, 3/31/14

Class Materials

• lab_01a.md
• lab_01a_example.md
• lab_01b.md
• lec_01.pdf

Data Collection and Extraction

Wednesday, 4/7/14

Project 1 Introduced

• Description for Project 1

Class Materials

• Lecture
• Lab 2a
• Lab 2b
• Lab 2b - Code

Additional Resources:

#####Learning how to use the file pager, less

• Less Homepage

Python Documentation

Handy to have this in your bookmarks!

• https://docs.python.org/2.7/

Couple extra handy python introductions

• Interactive Python Training
• The Python Tutorial

Beautiful Soup Tutorials

• Beautiful Soup Documentation
• Deck on Beautiful Soup
• Greg Reda's Web Scraping 101

APIs to play with

• Handy Python APIs
• apigee Console

Numpy

Wednesday 4/9/2014

Class Materials

• IPython Notebook Introduction
• Numpy and Pandas Introduction

Additional Resources

• Watch the 5 minute "Ipython Notebook Tour"
• Review "What is NumPy"
• Watch Wes McKinney's 10 minute Whirlwind Tour of Pandas (even once is ok ;-) )
• Another great resource: Review Chapters 1 to 5 of Julia Evans Cookbook

Pandas

Monday 4/14/2014

Class Materials

• Python Data Review

• Lab - Practical Pandas

• Numpy and Pandas Introduction

• Pandas Practice

Data Visualization and MatPlotLib

Wednesday 4/16/2014

Class Materials

Lecture Notes: Data Visualization

Python Notebook: Plotting with Matplotlib

Assignments Due

• Complete and submit previous assignments

Additional Resources

Resource	About
Basic Plotting in Pandas
Matplotlib userguide
Matplotlib Gallery	Examples with Code
Rougier and Prace EuroSciPy Matplotlib Tutorial	Short Overview

Exploratory Data Analysis

Monday 4/21/2014 We'll be reviewing a number of datasets and going through the Data Exploration Process

The ACES model for Data Exploration:

Letter	Step	Notes
A	Assemble the data frame	Find data, import into Pandas
C	Clean the data frame	Identify and limit columns, rows, indices, dates, etc.
E	Explore global properties	Visualize! Basic plots and stats appropriate to the data set
S	Subset comparisons	Look at (visualize!) initial emergenet variable relationships and subsets

Class Materials

• EDA Run Through - IMDB

Resources

• EDA with SAT Scores
• Grouping with Pandas
• Data Wrangling Movies
• EDA Questions
• Volinksy EDA Presentation

Assignments Due

N/A - Please review all prior materials and work on Project 1.

Presentations, Machine Learning, and Data Science Careers

Wednesday 4/23/2014

Assignments Due

[Project 1: Scraping, APIs, and Data Visualization](Project 1https://github.com/datadave/GADS9-NYC-Spring2014-Lectures/blob/master/projects/project01.md)

Class Outline

• Selected Presentations of Student Projects
• Discussion of Data Science Careers
• Introduction to Machine Learning