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Social Network Analysis Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
1 months
Duration
1 months
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

This Social Network Analysis course offered by Coursera in partnership with UC Davis is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. 

Overview

 Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). 

While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. 

This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the Social Network Analysis course offered by Coursera in partnership with UC Davis, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics.

What you'll learn

  • Define networks and discover the languages networks use.

  • Analyze a social network through data wrangling and visualizing a network.

  • Discuss what mechanisms generate networks.

  • Examine social networks analysis using case studies.

Programme Structure

Course structure:

  • Data Wrangling
  • Network Measures 
  • Network Measures 
  • Influentials
  • Who's Influential?
  • Twitter Cascades

Key information

Duration

  • Part-time
    • 1 months
    • 3 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • Beginner level
  • No previous experience necessary

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • Audit: free access to course materials except graded items
  • Certificate: a trusted way to showcase your skills
  • A year of unlimited access with Coursera Plus $199

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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