Skip to content

Latest commit

 

History

History
68 lines (35 loc) · 3.06 KB

0-environment.md

File metadata and controls

68 lines (35 loc) · 3.06 KB
Raw

Development Environment

This page starts with installing Python, and then dives into all the tools and programs that you will be using daily.

Table of Contents

1. Python

2. Command Line

3. Text Editors

4. Git

5. Jupyter Notebook

6. Assignments

1. Python

Anaconda is the leading data science platform for Python. The open source version of Anaconda is a high performance distribution of Python and includes over 100 of the most popular Python packages for data science. Download the graphical installer for Python 3.X.

2. Command Line

If you are serious about a career that involves programming, you need to start getting comfortable using the Command Line Interface. It was the main style of inteface for computers before Mice and graphical operating systems were invented. If you are old enough to have used MS-DOS, you know what I'm talking about!

Get Started - Level Up: Command Line Basics

(Optional) - Comprehensive Overview - Learn Enough: Command Line

3. Text Editors

You will probably spend most of your time with access to a graphical interface, where you have more choices in editors and integrated development environments. We recommend the Atom Text Editor.

Get Started - Level Up: Atom Text Editor

(Optional) Comprehensive Overview - Learn Enough: Text Editor

4. Git Version Control

Git is a version control system; think of it as a series of snapshots (commits) of your code. You see a path of these snapshots, in which order they where created. You can make branches to experiment and come back to snapshots you took. GitHub, is a web app on which you can publish your Git repositories and collaborate with other people.

Introduction to Version Control and the GitHub Desktop App

(Optional) Comprehensive Overview - Learn Enough Git

5. Jupyter Notebooks

The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. You will be using the Jupyter Notebook almost every day of the bootcamp.

To start a Jupyter Notebook server, type "jupyter notebook" in a empty folder from your command line.

A short video tutorial.

6. Assignments

  1. Complete all the guides and tutorials on this page.