If you do not yet code and want to learn, this Specialization has a goal to soften the learning curve for Python. It has four main objectives:
To inspire you to code
To help you think in code
To teach you technical concepts to code
To give you useful examples of things to do in code
There is a steep learning curve on learning to code, and that is why this Specialization emphasizes motivation. You have to want to learn to code and stick with it through multiple learning activities and your own experimentation, research, and practice. This single Specialization will not teach you to code. It will, however, get you started with a mindset for coding, understanding of Python technical concepts, and an appreciation of what can be done with Python to access and interact with data on the Internet. These skills are increasingly essential for researchers.
The wealth of data that is now available to researchers who can use Python and other tools to access it is transforming academic disciplines, including the social sciences. But there's a gap between the questions about human nature that we know internet data can cast light on, and the raw, messy reality of code and data. Each course in this Specialization has code demonstrations that you run that show how to use Python to bridge the gap and to discover things about ourselves, our friends, each other, and society, as we interact with the Internet in code.
We look forward to being a part of your continuing education!
Applied Learning Project
While no formal requisites are necessary to join this specialization, you will be accessing and completing assignments in Jupyter Notebooks using the programming language Python in various APIs. On the technical skills side, this specialization will teach basic Python types, variables, code flow, and modules, up to functions.
