explanation
The Computational Social Science specialization is a social computational science course. Digital technology has not only changed society, but it has also changed the way we view society. The increase in human communication is leaving a huge digital footprint. Investigating them can provide unique insights into what society is and how it works, including complex social networks that have long been obscure. Computer computing power allows us to identify hidden patterns with the help of statistical tools such as machine learning.
Here’s what you’ll learn in the Computational Social Sciences specialization series:
- Learn how to build recognizable social systems and patterns in social networks and human dynamics.
- Define and discover the opportunities and limitations of metadata.
- We scrape online data from the web, use it to build visualizations of social networks, and use machine learning to analyze that content.
- Use computer simulations to plan your own mock community and discover business strategies.
Course details:
Publisher: Coursera
teacher: martin hilbert
Language:English
Education level: Introductory
Number of courses: 5
Period: Assuming 3 hours per week, 6 months
Courses in the Computational Social Science Specialization Series:
Course 1
Computational social science methods
Course 2
Big data, artificial intelligence, and ethics
Course 3
social network analysis
4 courses
computer simulation
5 courses
Computational Social Science-Capstone Project
Course Prerequisites:
No background is required to pursue this specialization.
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This collection includes five different courses.
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Computational Social Science Methods 2021-4
Big Data, Artificial Intelligence and Ethics (2021-4)
Social Network Analytics 2021-4
Computer Simulation 2021-4
Computational Social Science Capstone Project 2021-4
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1.4GB + 2.1GB + 1.4GB + 1.4GB + 374MB