Learn to create and analyze agent-based models and artificial societies using computational tools for social science research.
Learn to create and analyze agent-based models and artificial societies using computational tools for social science research.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Computational Social Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.4
(80 ratings)
8,686 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
What you'll learn
Create agent-based models using NetLogo
Analyze complex social systems through simulation
Develop theoretical models of social phenomena
Implement and modify artificial societies
Evaluate computational social science theories
Skills you'll gain
This course includes:
6.3 Hours PreRecorded video
5 quizzes, 1 peer review
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course introduces students to computer simulations in social science research. The curriculum covers agent-based modeling, artificial societies, and theoretical exploration through computational tools. Students learn to use NetLogo to create and analyze social simulations, including famous models like Schelling's segregation model and Sugarscape. The course emphasizes hands-on experience with building artificial societies and understanding complex social phenomena through simulation.
Getting Started and Computer Simulations
Module 1 · 3 Hours to complete
Artificial Societies: Sugarscape
Module 2 · 2 Hours to complete
Computer Simulations and Characteristics of ABM
Module 3 · 1 Hours to complete
Model Thinking and Coding Artificial Societies
Module 4 · 4 Hours to complete
Fee Structure
Instructor
Professor and Chair DE Computational Social Science
Martin Hilbert is a distinguished Professor at the University of California, Davis, specializing in the intersection of digital information and algorithms within complex social systems. He holds dual doctorates in Economics and Social Sciences (2006) and Communication (2012). His academic contributions include pioneering studies on the global information landscape and developing the first digital action plan for Latin America and the Caribbean during his tenure as an Economic Affairs Officer at the United Nations. Hilbert's foresight in recognizing the implications of digital manipulation was evident when he alerted the public about Cambridge Analytica's involvement in political campaigns a year before it became widely known.In addition to his research, Dr. Hilbert teaches various courses, including Big Data, Artificial Intelligence, and Ethics, as well as Computational Social Science methods. His work has been published in leading academic journals and featured in prominent media outlets such as The Wall Street Journal and The Economist. With a rich background that includes providing technical assistance to over 20 countries, he is fluent in five languages and has traveled extensively across four continents, bringing a global perspective to his research and teaching.
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4.4 course rating
80 ratings
Frequently asked questions
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