This repo includes materials for the General Assembly Data Science course in NYC. Navigate the directory structure to find what you're looking for. The README.md files are often the most central in a directory, and will display by default when you navigate on github. This page is also linked via bit.ly/gadatascience
9/3/2014 : Introduction To Data Science
9/8/2014 : Data Collection And Extraction
9/10/2014 : Numpy
9/15/2014 : Pandas
9/17/2014 : Data Visualization in Python
9/22/2014 : The A.C.E.S. Framework for Data Exploration
9/24/2014 : Hypothesis Testing with Data
9/29/2014 : Data Results
10/1/2014 : Unit 1: Project Presentations
10/6/2014 : Intro to Machine Learning / Linear Models
10/8/2014 : Logistic Regression
10/13/2014 : NO CLASS
10/15/2014 : Natural Language Processing
10/20/2014 : Naive Bayes
10/22/2014 : Decision Trees and Random Forests
10/27/2014 : PCA, KPCA
10/29/2014 : K Means
11/3/2014 : Unit II Project Presentations
11/5/2014 : Databases
11/10/2014 : Data Products (flask, maps )
11/12/2014 : Course Review
11/17/2014 : Final Project Workshop
11/19/2014 : Final Project Presentations!
## Admin ### Unofficial Text(s) * [Python for Data Analysis](http://shop.oreilly.com/product/0636920023784.do) * [An Introduction to Statistical Learning (with Applications in R)](http://www-bcf.usc.edu/~gareth/ISL/) ### Getting Help **Github Issues** For general or specific course help, students can get the fastest response by posting an issue, to the [issues page for this repository](https://github.com/TeachingDataScience/data-science-course/issues) * Chris will be reviewing each issue and will assign it to Ed, Dave or himself. * Students and other instructors following the repository will also be able to address the issue, improving response time. **Office Hours** Ed and Dave will hold regular office hours, and Chris will hold regular weekend sessions. Dave's office hours are posted [here](https://accounts.google.com/ServiceLogin?service=cl&passive=1209600&continue=https://www.google.com/calendar/selfsched?sstoken%3DUUJjNUJzODlzeDdPfGRlZmF1bHR8MTQ3MjQwYzU4M2M3NmFkODRhMTdhN2Y1MDNlNjE2NGI&followup=https://www.google.com/calendar/selfsched?sstoken%3DUUJjNUJzODlzeDdPfGRlZmF1bHR8MTQ3MjQwYzU4M2M3NmFkODRhMTdhN2Y1MDNlNjE2NGI&scc=1), and slots can be signed up for electronically. Ed's office hours are posted [here](https://www.google.com/calendar/selfsched?sstoken=UUowVUZtNDJlNGlJfGRlZmF1bHR8MDUxMjk5YmEzMDQyMTJkN2ZjZjY3NmUwNmVkMWZiNzg), and slots can be signed up for electronically. Chris' regular weekend sessions will be held at GA West on Saturdays from 10:30a-12:30p. There is no need to sign up, but if you have something specific you want to discuss, feel free to [email me](mailto:rwc.sheehan@gmail.com?subject=DAT13%20Office%20Hours) ahead of time. ### Communication #### Watch the Github Repository In order to see issue notifications you need to 'watch' the github repository. You can tailor your settings to receive notifications via email, daily, weekly, etc. If you're not already "watching" the github repository, please do so. You can check the [watcher's list](https://github.com/TeachingDataScience/data-science-course/watchers) to see if you're on it. And if you're not on it, you just need sign in to github, and then to click the watch button from that same page.  ### Assignments #### Assignment Folder * Instructions for each assignment is listed in the [assignments folder](assignments/) #### Submitting Assignments * Linkable assignments, such as gists, can be submitted by posting to [this submission form](https://docs.google.com/forms/d/1TzvQCYruLcTLzfCQBcjhp7INLZWvwErCqTaFCU7LhpE/viewform?usp=send_form).