This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. Learners who complete this specialization will be prepared to take the Data Science: Statistics and Machine Learning specialization, in which they build a data product using real-world data.

The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization. This specialization is presented for learners who want to start and complete the foundational part of the curriculum first, before moving onto the more advanced topics in Data Science: Statistics and Machine Learning.

Necessary preparation

• No prior experience required.

The Program

1. The Data Scientist’s Toolbox.
2. R Programming.
3. Getting and Cleaning Data.
4. Exploratory Data Analysis.
5. Reproducible Research.

What you will learn

• Use R to clean, analyze, and visualize data.
• Use GitHub to manage data science projects.
• Learn how to ask the right questions, obtain data, and perform reproducible research.
• Set up R, R-Studio, Github and other useful tools.