Perfect for beginners, this course will teach you the fundamentals of Python programming through taught materials and practical example
By the end of this course you will:
Develop skills with core elements of the Python programming language, and gain an appreciation of how these can feed into social scientific work (e.g., researching with digital data).
See how to make methodologically appropriate decisions when designing and developing research where programming skills are deployed, including harvesting and organizing data.
Understand how to approach a social science research question using Python, and have the capacity to devise a solution to such problems where programming skills can be deployed to reveal social scientific insight.
To reinforce these learning objectives we include a number of structured activities to follow on from the learning objectives.
Here we cover how to install Python and how to use it from an IDE or in the shell we demonstrate the concepts equality and comparison as well as assigning variables
We expand on module 1 by covering different data types and string formatting we then cover three of the basic containers Python offers which are lists, dictionaries and tuples
In this module, we look at some key syntax which is if else conditions, and or conditions, for and while loops and lastly show how we can deal with files
In the last module we look at how to work in the web and look at objects and classes, we show how we can put together code in functions and scripts and look at how you should think like a programmer
None. This course would work for someone with no prior computing knowledge but would also be suitable for individuals with experience in other languages. An understanding of file paths and file management is important.
You will have 3 months’ access to this course.
The course is organized into a set of interactive learning modules, and you should work through the modules sequentially. The modules contain a number of topic pages, each including a video to walk you through the concept and interactive text to reinforce what was covered in the video, quick questions and knowledge checks.
There are three additional types of activity throughout the course to facilitate deeper learning:
Match: These activities require you to have a go at a task offline, then select the correct solution.
Guided: These are multi-part match activities so you do a part of the task then submit your solution, which unlocks feedback on your attempt and the next part of the task.
Structured: This is a more extended offline task, which you should attempt before seeing the Tutor’s solution.
The vast majority of topics in the course are fundamentally practical. You are strongly encouraged to recreate and run the code as you work through them, and complete knowledge checks and activities.
You should install Anaconda 4.4+ and PyCharm
No they are either open source or have community (free) versions
A computer or laptop with the suggested software and a modern browser e.g. Internet Explorer 10+ or the latest versions of Chrome and Firefox.
You don't need the book for completion of the course (everything you need to learn is included within your modules), but there are sections of the course where you might find it interesting to do a little outside reading. Learners on the course get a 30% discount (or 25% discount for those based in Australasia) for Phil's book; Programming with Python for Social Scientists.
While you can access the course on your mobile device, go through the content and answer questions, you will need a desktop or laptop computer to practice and complete the activities that require you to write and/or test code.
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