Transcript

RUTH ALEXANDER

Hello again. You've now reached the end of this course on 'learning to code for data analysis'. You've seen and experienced some of the fundamentals of programming such as basic data types and structures like numbers, strings and lists and assignments and variables to store intermediate results. You've also seen the basic techniques to obtain, clean, transform, aggregate and visualise data. With a single line of code you can filter out the missing values, join two tables or make a chart. Finally you have seen how to use interactive notebooks to write up your own data analysis as a mixture of explanatory text and runnable code.

Notebooks can be easily shared among a group of colleagues or publicly which means you can make a real contribution to ongoing research and debates. We hope you're keen to apply your newly gained skills to other data sets on issues that you care about. You'll be able to find data sets you can explore and interrogate in the fields of health, education, energy, climate change, poverty, crime and many more besides. Below this video you'll find links to open data sources but don't forget that your national government or even your local authority might provide open data that's more relevant to you. In a short course like this we could only scratch the surface of coding and data analysis.

We hope to have inspired you to learn more about programming, data science and data management, or even statistics. Below you'll also find links to Open University courses, qualifications and free online resources that are related to the topics of this course. Whether you continue your studies with the Open University or not we do hope you really enjoyed learning to code for data analysis. We'd love to hear your feedback and suggestions. Thanks for participating and all the best for the future.