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Overview


Introduction to Data Science for Social Scientists

Next course runs from [[date]]

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Overview


Introduction to Data Science for Social Scientists

Next course runs from [[date]]

Course overview

This introductory course provides all the theory and information you need for understanding data science methods from a social science perspective. Comprised of four manageable modules, this course is perfect for busy people who want to gain knowledge of the discipline before committing time to learning how to program. If you're looking to learn the ‘whys’ and the ‘whats’, before tackling the ‘hows’, then this is the course for you.

This course is also suitable for those who already have coding skills, but want to learn how to apply these in a social science context.

You will learn:

  • How data science is changing social science and statistics

  • About data science ethics and the potential issues with data collection and data sources. You will also consider the issues of privacy, sampling, population size, interpretation, and application

  • How to construct a survey and crowdsource responses, and which free tools you can use to build surveys

  • Which data science tools are commonly used in social science research

  • The value of open-source programming languages, specifically R and Python, and the advantages and disadvantages of each

  • How to work in Jupyter notebooks, a browser-based tool for creating interactive documents with live code, annotations, and visualizations - an ideal tool for helping you gain data science skills

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Introduction to Data Science for Social Scientists

Effort
10 hours
Prerequisites
None, this course is suitable for all. A basic foundation in statistics would be helpful, but it is not essential.
Instructors
Dr. Claudia von Vacano, Dr. Christopher Hench, Geoff Bacon, Dr. Evan Muzzall, Dr. Laura Nelson, Dr. AdDr. am Anderson, Professor David Harding and Rachel Janson
In association with
Social Science Data Lab (D-Lab) at the University of California, Berkeley
Language
English
 
299.00
Start date:
Enroll
299.00
Start date:
Enroll

Course Instructors


Course Instructors


Course Instructors

 

 
 

How It Works


How It Works


How It Works

You have access to the course for 3 months. For the first 8 weeks of the course there will be fortnightly video Q&A sessions. In these live sessions, you will have the opportunity to ask your instructor questions, or discuss a topic you may be struggling with.

 
 

Syllabus


Syllabus


Syllabus

Module 1 - Introduction and overview to data science

This module will provide a social science perspective on data science, introducing you to the objectives of the course via a visual overview of each module. It will discuss how data science is changing social science and statistics, and will cover reliability, generalizability, and reproducibility.

Module 2 - Ethics in data science

This module will teach you about the shortcomings and problems of data science in respect to the groups of people it affects, who it’s representing, and how to responsibly acknowledge these issues in research. Beyond problems in data collection and data sources are issues of privacy, sampling, population size, interpretation, and application. This module importantly emphasizes issues of deidentification and reidentification, and data security.

Module 3 - Surveys and crowdsourcing data

This module will give an overview of how to construct a survey and crowdsource responses. Specifically, you will be introduced to Qualtrics and learn about other freely available tools for building surveys. We will discuss Amazon’s Mechanical Turk, which is becoming the new norm for online data collection in the social sciences.

Module 4 - Data science tools

This module will introduce you to the data science tools commonly used in social science research. We will discuss the value of open-source programming languages, specifically R and Python, for research of this nature and weigh the advantages and disadvantages of each.

This module introduces Jupyter notebooks, and concludes with a brief overview of Git and GitHub as they have become essential for collaborative research programming projects.

In association with


In association with


developed in association WITH

FAQs


FAQs


Frequently Asked Questions

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

Will I be learning how to program?

This course will introduce you to Python and R - and discuss the pros and cons of both languages - but it is not intended as a comprehensive programming course. In the final module you have the opportunity to ‘have a go’ at programming code. If this inspires you to learn how to code, we recommend taking our forthcoming FUNdamentals of Data Science with R or FUNdamentals of Data Science with Python.

Do I need to install any software?

Only if you want to! In the final module you have the opportunity to try some coding but this can take place in the JupyterHub. Using the JupyterHub means that all of your programming takes place in your web browser on your computer, tablet, or phone. However, if you wish to install R or Python please do!

How long will I have access to the course for?

You have access to the course for 3 months. For the first 8 weeks of the course there will be fortnightly video Q&A sessions. In these live sessions you will have the opportunity to ask your instructor questions, or discuss a topic you may be struggling with.

Will I 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.

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Introduction to Data Science for Social Scientists
299.00
Start date:
Enroll