The Data Scientist’s Toolbox

1 week to complete at 10 hours a week
Flexible Schedule

Jeff Leek, PhD , Roger D. Peng, PhD , Brian Caffo, PhD

What You’ll Learn

Set up R, R-Studio, Github and other useful tools

Understand the data, problems, and tools that data analysts use

Explain essential study design concepts

Create a Github repository

Skills You’ll Gain

Rmarkdown Git (Version Control System) Development Environment GitHub Data Science Big Data R Programming Version Control Data analysis Integrated Development Environments Software Installation Statistical Programming

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile.

Develop Your Specialized Knowledge

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate

There are 4 modules in this course

In this module, we'll introduce and define data science and data itself. We'll also go over some of the resources that data scientists use to get help when they're stuck.

In this module, we'll help you get up and running with both R and RStudio. Along the way, you'll learn some basics about both and why data scientists use them.

During this module, you'll learn about version control and why it's so important to data scientists. You'll also learn how to use Git and GitHub to manage version control in data science projects.

During this final module, you'll learn to use R Markdown and get an introduction to three concepts that are incredibly important to every successful data scientist: asking good questions, experimental design, and big data.