Introduction to Python for Social Scientists

Next course runs from 11 September 2017 - 8 October 2017



Introduction to Python for Social Scientists

Next course runs from 11 September 2017 - 8 October 2017

Course overview

This course will introduce you to the Python programming language. Through the use of taught material and practical examples, you will learn how to build up the skills needed to perform data analysis using Python. The course will familiarize you with key tasks that can be performed using the Python language and will equip you to make the right decisions when dealing with and manipulating data using the software. The course culminates with a structured data analysis task.

Course objectives

By the end of the course you will be able to:

  • Perform tasks using elements of the core Python language and some commonly used Python packages
  • Make the right decisions when approaching programmatic tasks including dealing with and manipulating data. 
  • Understand a data analysis problem, develop a strategy to tackle the problem, and devise a solution using Python


Any questions? - Contact us

For a bulk order of 5 or more learners on any of our courses, you can claim 50% discount. Contact us for more information.

Introduction to Python for Social Scientists

On average this course will take 12 hours to complete including activities. The following average time commitment is required each week: Week 1: 2h30 Week 2: 2h30 Week 3: 3h00 Week 4: 3h30 - 4h00
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.
Dr Rob Mastrodomenico and Dr Phillip Brooker
In association with
Royal Statistical Society
Start Date:
Start Date:

Course Instructors

Course Instructors

Course Instructors


How It Works

How It Works

How It Works

The course is organised into a set of interactive learning modules. You should work through the modules sequentially.

The interactive learning modules contain a number of topic pages. Each topic page has a video to walk you through the concept, and interactive text such as guide questions and knowledge check, to reinforce what was covered in the video.
There are three additional types of activity in your course to facilitate deeper learning. These are presented in the relevant topic pages

  • 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, where 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 complex offline task. To see the tutor’s solution you need to share your attempt at the task and your reasoning. You also get to see other participants' attempts and are encouraged to engage in discussion. The tutor will then share further feedback

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, completing knowledge checks and activities.

This course comes with learner support for the dates this course runs. After the course ends, you’ll still have access to the course materials but you won’t receive support from the instructor. 

It is recommended that learners:

  • Complete Modules 1 & 2 in week 1
  • Complete Module 3 in week 2
  • Complete Module 4 in week 3 
  • Complete Module 5 in week 4




Module 1

In this Module, you’ll cover the following:

Why use Python?

  • Introduction to the course and a short explanation of the value of Python for data analysis and social science

Installing Python

Working in the shell and using an editor

  • Overview of using the Python shell (and IDLE for Windows) to write code

Module 2

In this Module, you’ll cover the following:

Equality and comparison

  • Difference between assignment and equality, using comparison operators

Data Types

  • The three different data types and operations that can be performed on them.

Assigning variables

  • Assigning one or more variables, overwriting and modifying variables

String formatting

  • String use and manipulation in Python


  • Creating and manipulating lists, list functions and mapping

Module 3

In this Module, you’ll cover the following:


  • Function and use of the tuple data container


  • Function and use of dictionaries

IF statements


  • Constructing and using loops and if statements to check conditions and change the behaviour of a program


  • Using and/or conditions

Module 4

In this module you’ll cover the following:
Dealing with files

  • Opening, reading and closing files

 Working with the web  

  • Pull data from web

Writing scripts in python              

  • Splitting code into multiple scripts

Writing functions

  • Purpose and use of functions

 Objects and Classes   

  • Creating a class and using objects

Module 5

In this module you’ll cover the following:


  • Use Pandas data frames to deal with multi-level data


  • How to plot graphics using this package

A brief guide to thinking like a programmer

  • Considerations when planning tasks to do using code, task flow etc.

 Data analysis challenge

  • This will set out and guide an exploratory data analysis activity. It will be set out as a series of tasks completed one at a time

Debrief and parting thoughts

  • Reviewing the course and further considerations for social science

In association with

In association with

developed in association with



Frequently Asked Questions

Please see below for answers to some of the most frequent questions we get about this course.

What software do I need for this course?

You should install Anaconda 4.4+ and PyCharm

Do I need to buy any of this software?

No they are either open source or have community (free) versions

What do I need to participate on this course?

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.

Can I do this course on my mobile device?

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.

How long will I have access to the course for?

The course will be run over 4 weeks, during which you will have access to learning support provided by the course instructor. After the 4 weeks, you will still have access to the course materials for another 2 months, but you will not be able to receive learning support from the instructor, and if there is a course forum, you will not be able to ask any questions.

Do learners get a certificate?

All of our courses offer a certificate of completion signed by your instructor. You will be able to download this certificate, from the Learning Platform, when you complete the course.

Can't find what you're looking for?