This course is part of Computational Social Science.
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.
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English
پښتو, বাংলা, اردو, 2 more
What you'll learn
Master web scraping techniques for social media data collection
Visualize and analyze complex social networks
Apply machine learning for natural language processing
Develop computer simulations of social behavior
Integrate multiple computational methods for social analysis
Skills you'll gain
This course includes:
1.95 Hours PreRecorded video
1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive capstone project integrates multiple computational methods to analyze social phenomena. Students collect data through web scraping, visualize and analyze social networks, perform sentiment analysis using NLP, and create computer simulations to model social behaviors. The course demonstrates practical applications of computational tools in social science research, preparing students to conduct data-driven social analysis using modern computational methods.
Getting Started and Milestone 1
Module 1 · 4 Hours to complete
Milestone 2: Social Network Analysis
Module 2 · 2 Hours to complete
Milestone 3: Natural Language Processing
Module 3 · 2 Hours to complete
Milestone 4: Agent-Based Computer Simulations
Module 4 · 4 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Computational Social Science
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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