dsp's Introduction

Data Science Bootcamp Pre-work Revision 2019

Table of Contents

1. Computer Requirements
2. Overview
3. Pre-work Exercises
4. FAQs

1. Computer Requirements

Review the computer requirements on hardware needed for the bootcamp.

2. Overview

What can I do to get ready before the bootcamp starts?

Completing the pre-work is essential to obtaining the foundational knowledge necessary to succeed in the Metis data science bootcamp. Each student should expect to spend 60+ hours of tutorials to become familiar with software installation, editors, command line, Python (numpy, pandas, etc.), linear algebra and statistics.

3. Pre-work Exercises

All exercises must be completed before the first day of class.

Step 0. Getting Started
- Step 0a. Markdown
- Step 0b. Fork GitHub Repo
Step 1. Installation
- Step 1a. Install software on your computer
- Step 1b. Install Jupyter Notebook on your computer
Step 2. Choose and learn your editor(s)
Step 3. Learn command line
Step 4. Git and GitHub
- Step 4b Git Branching
Step 5. Python
- Step 5a. Learn Python
- Step 5b. Advanced Python
- Step 5c. Python Pandas
Step 6. Linear Algebra
Step 7. Statistics
Step 8. More Resources

4. FAQs

Q: How do I submit pre-work?

Sections 0 to 4
- Fork the dsp repo this is covered in the GitHub section
- Clone your forked dsp repo to your local PC
- Run Jupyter on your local and make all changes
- Push all changes to your forked repo on GitHub; this is considered your pre-work submission. (No need to submit pull requests to the thisismetis/dsp repo.)
Python
- use your forked repo for scratch work only
Statistics
- Make all changes to your forked repo