• The Open University

Learn to Code for Data Analysis

Learn to code in Python using Jupyter Notebook. Use your new programming skills to analyse and visualise open data.

79,306 enrolled on this course

Learn to Code for Data Analysis
  • Duration4 weeks
  • Weekly study5 hours

Learn to code in Python and analyse real, open data

This hands-on course will teach you how to write your own computer programs, one line of code at a time. You’ll learn how to access open data, clean it and analyse it, and produce visualisations. You will also learn how to write up and share your analyses, privately or publicly.

You will install free software to learn to code in Python, a widely used programming language. You will write up analyses and do coding exercises using the popular Jupyter Notebook platform. And you will look at real data from the World Health Organisation, the World Bank and other organisations.

What topics will you cover?

  • Python: variables, assignments, expressions, basic data types, if-statement, functions
  • Programming: using Jupyter Notebooks, writing readable and documented code, testing code
  • Data analysis: using pandas to read CSV and Excel files, to clean, filter, partition, aggregate and summarise data, and to produce simple charts

What will you achieve?

By the end of the course, you‘ll be able to...

  • Demonstrate an understanding of basic programming concepts.
  • Using a programming environment to develop programs.
  • Develop an awareness of open data sources as a public resource.
  • Produce and write simple programs to analyse large bodies of data and produce useful results.

Who is the course for?

The course does not assume prior experience in programming or data analysis. Basic familiarity with a spreadsheet application will be an advantage.

The course does not require any knowledge of statistics, but you need to have basic numeracy skills, like writing arithmetic expressions, using percentages and understanding scientific notation. If you wish to brush up on your numeracy skills, we recommend the FutureLearn course Basic Science: Understanding Numbers from The Open University.

What software or tools do you need?

To study this course you will use specialist software. You can use the software online, via a free account on a website, or offline, by downloading and installing a free software package. You will receive instructions about both options via email before the course starts. The online solution requires a good internet connection and has some limitations.

The offline software has no limitations and is the recommended option. However, you will need access to a desktop or laptop computer on which you can install software. The software is free and there are versions available for Windows, Mac and Linux platforms. You will need about 3 GB of free disk space to download and install the software, and to store datasets that will be provided in the course.

Whether you choose the online or offline software option, you will need to be proficient in basic computer tasks, like creating folders, downloading files and copying them to specific folders, etc. In terms of accessibility, you will be asked to use your web browser and to type code.

What do people say about this course?

Excellent course, being a developer for a number of years it gave me insight into manipulating large sets of data and as I am taking other courses related to data visualization I am looking forward to new technologies. Thanks!

Goran Papic

I wanted to say to the course designers and mentors that I enjoyed the course. I think it was well structured and a nice, progressive pace and degree of difficulty. There were a few moments where details and syntax seemed to escape me, but Chris offered encouragement and that was a benefit of the group-chat-discuss approach. It showed me a tool and its application to dice and slice and make some sense out of "spreadsheet type" data. I have a data base background -no or very limited Excel- and found the course different and useful. It's a challenge for a retiree to take on a new subject and tools, but I'm glad to have done it successfully.

Jack Drawbridge

Who will you learn with?

Michel does research on software maintenance. He likes producing OERs (www.open.edu/openlearn/profiles/mw4687), looking at data visualisations and playing German-style board games.

My research is on designing integrated programming / learning environments for students new to programming.

Open University academic and open data geek, with interests in data visualisation, data journalism and open education. Regular blogger at blog.ouseful.info

Who developed the course?

The Open University

The Open University (OU) is the largest academic institution in the UK and a world leader in flexible distance learning, with a mission to be open to people, places, methods and ideas.

  • Established1969
  • LocationMilton Keynes, UK
  • World rankingTop 510Source: Times Higher Education World University Rankings 2020