Computational Social Science Methods is a course that provides an overview of the current opportunities and reach of computational social science. It delves into the impact of the digital revolution on social science, covering topics such as artificial intelligence, social networks, and human dynamics. The course aims to equip students with the necessary skills to analyze social systems using computational tools.
What You’ll Learn
- Examine the history and current challenges faced by Social Science through the digital revolution.
- Configure a machine to create a database that can be used for analysis.
- Discuss what is artificial intelligence (AI) and train a machine.
- Discover how social networks and human dynamics create social systems and recognizable patterns.
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Skills You’ll Gain
- Data Science
- Big Data
- Python Programming
- Github
- Machine Learning
- Deep Learning
- Methodology
- SQL
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This course explores the intersection of social science and computational methods, focusing on the current challenges and opportunities brought about by the digital revolution. The curriculum covers a wide range of topics, including artificial intelligence, machine learning, social networks, and computer simulations.
Throughout the course, students will gain hands-on experience in configuring machines to create databases for analysis and training machines using artificial intelligence. They will also learn how social networks and human dynamics create recognizable patterns in social systems.
Key highlights of the course:
- Gain insight into the history and challenges faced by Social Science in the digital era.
- Learn to configure machines for database creation and analysis.
- Explore artificial intelligence and its role in analyzing social behavior.
- Discover the impact of social networks and human dynamics on social systems.
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