subject

FutureLearn: Learn to Code for Data Analysis

 with  Michel Wermelinger

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 to produce visualisations. You will also learn how to write up and share your analyses, privately or publicly.

You will install free software (see Requirements below) to learn to code in Python, a widely used programming language across all disciplines, due to its support for scientific and engineering libraries and visualisation tools, and wide range of development tools.

You will write up analyses and do coding exercises using the popular Jupyter Notebooks platform, which allows you to see immediately the result of running your code and helps you identify – and fix – any errors more easily.

You will look at real data from the World Health Organisation, the World Bank and other organisations. You’ll be encouraged to discuss the data and your analyses with your fellow learners, and to build a community of researchers around these and other datasets.

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.

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.

3 Student
reviews
Cost Free Online Course (Audit)
Pace Upcoming
Subject Data Analysis
Institution The Open University
Provider FutureLearn
Language English
Certificates $49 Certificate Available
Hours 3 hours a week
Calendar 4 weeks long
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FAQ View All
What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

3 reviews for FutureLearn's Learn to Code for Data Analysis

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10 months ago
Natrina completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
This is a course for getting your feet wet in data analysis with Python. At first I was afraid it would be too introductory, but you actually get to do some of the basic tasks required for data analysis. Some basic knowledge of Python may make this course a bit more useful and easier to understand, and you can take it Read More
This is a course for getting your feet wet in data analysis with Python. At first I was afraid it would be too introductory, but you actually get to do some of the basic tasks required for data analysis. Some basic knowledge of Python may make this course a bit more useful and easier to understand, and you can take it further if you take the time to do all the tasks they suggest and develop a project of your own.
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a year ago
Colin Khein completed this course.
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7 months ago
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Joe R completed this course.
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