• Specialization: Core Concepts in Data Science
  • Instructor: Jane Wall
  • Prior knowledge needed: Basic knowledge of R programming; Knowledge of R Studio also helpful

View on Coursera

Learning Outcomes

  • By taking this course, you will be able explain what data science is and identify the key disciplines involved.​
  • You will be able to use the steps of the data science process to create a reproducible data analysis and identify personal biases.​
  • You will be able to identify interesting data science applications, locate jobs in Data Science, and begin developing a professional network.​

Course Content

Duration 55m

This week we will talk about the past, present and future of data science.  The growth of data science has been fueled by the growth of the internet, social media and online shopping as well as by the rapid increases in data storage capabilities.  You will watch several short videos and participate in discussions about the future of data science.

Duration: 1h 28m

This week you will watch videos and have a reading on some applications of data science in industry and academia.  You will hear from data scientists in different fields to find out how they use data science.

Duration: 19h 14m

This week you will learn about the importance of reproducibility and how to achieve it, learn the steps in a data analysis process and learn about the possible pitfalls in data science.  You will watch demonstrating the various steps in the data science process and try out these processes for yourself on a different dataset.

Duration: 1h 28m

This week you will learn about important ways of communicating your results.  We will discuss the important things to know about presentations and reports.  You will also learn about the importance of networking and try it out.

Duration: 1h

You will complete a peer reviewed project worth 50% of your grade. You must attempt the final in order to earn a grade in the course. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.

Note: This page is periodically updated. Course information on the Coursera platform supersedes the information on this page. Click View on Coursera button above for the most up-to-date information.