Introduction

During the next year you will learn the fundamentals of data science. Surviving the nine courses which make up the Data Science Specialization offered by Johns Hopkins University requires a strategy. To this end, the focus of the ten-course series including a capstone project is to provide the learner with:

1. an introduction to the key ideas behind reproducible research,
2. an introduction to the tools and techniques to transform raw data into a presentable report,
3. an opportunity to gain hands-on practice so you can learn the techniques for yourself, and
4. an appreciation of the mathematics & statistics involved in data science.

Git is easy. Git is fun. Thanks Linus!

• Avro
• Harrier
• Hornet

Core Courses

The courses comprising the Data Science Specialization are:

• Data Scientist's Toolbox
• R Programming
• Getting and Cleaning Data
• Exploratory Data Analysis
• Reproducible Research
• Statistical Inference
• Regression Models
• Practical Machine Learning
• Developing Data Products

Figure 1 Course dependency diagram

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