About this Course

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Beginner Level

Approx. 14 hours to complete

English

Subtitles: English

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 14 hours to complete

English

Subtitles: English

Offered by

University of California, Davis logo

University of California, Davis

Syllabus - What you will learn from this course

Week
1

Week 1

4 hours to complete

Getting Started and Computer Simulations

4 hours to complete
11 videos (Total 85 min), 3 readings, 2 quizzes
11 videos
Course Introduction5m
Theoretical Simulations4m
Modeling and Mapping6m
Extending Thoughts Computationally (Part 1)6m
Extending Thoughts Computationally (Part 2)5m
Schelling's Segregation Model (Part 1)8m
Schelling's Segregation Model (Part 2)6m
Reflecting on Schelling5m
Expanding on Schelling (Part 1)6m
Expanding on Schelling (Part 2)9m
3 readings
About UCCSS10m
A Note From UC Davis10m
Agent Based Models (ABM)10m
2 practice exercises
ABM Quiz1h
Module 1 Quiz30m
Week
2

Week 2

3 hours to complete

Artificial Societies: Sugarscape

3 hours to complete
13 videos (Total 101 min), 1 reading, 1 quiz
13 videos
Sugarscape9m
Sugarscape Components4m
Sugarscape 24m
Sugarscape 3: Inequality (Part 1)7m
Sugarscape 3: Inequality (Part 2)11m
Sugarscape 4: Sex6m
Sugarscape 5: Inheritance7m
Sugarscape 6: Das Kapital10m
Sugarscape 7-10: Pressured to Move13m
Sugarscape 11-12: Sugar & Spice6m
Life on the Brink4m
The Generativist Motto12m
1 reading
Resources40m
1 practice exercise
Module 2 Quiz30m
Week
3

Week 3

2 hours to complete

Computer Simulations and Characteristics of ABM

2 hours to complete
12 videos (Total 75 min)
12 videos
CSS for Your Choices5m
Code You Can Live By7m
Gambling High or Low5m
More Risk in Your Life!8m
Today's Questions3m
Agent-Based Emergence (Part 1)7m
Agent-Based Emergence (Part 2)7m
Social Bursts5m
Intuitive Presentation4m
Context Sensitivity5m
Probabilistic Humbleness13m
1 practice exercise
Module 3 Quiz30m
Week
4

Week 4

5 hours to complete

Model Thinking and Coding Artificial Societies

5 hours to complete
15 videos (Total 118 min), 2 readings, 2 quizzes
15 videos
Four Model Outcomes (Part 1)5m
Four Model Outcomes (Part 2)10m
Analytical and Numerical10m
All Models Are Wrong10m
Occam's Razor5m
Science: Pure Creativity10m
Agent Based Models Lab Introduction47s
First Turtle7m
Moving Turtle9m
Communicating Turtles12m
Social Epidemiology8m
Conceptual Model6m
Changing People's Health9m
Computer Simulations of the Dead7m
2 readings
Welcome to Peer Review Assignments!10m
Optional / Voluntary / Complementary50m
1 practice exercise
Module 4 Quiz30m

About the Computational Social Science Specialization

For more information please view the Computational Social Science Trailer Digital technology has not only revolutionized society, but also the way we can study it. Currently, this is taken advantage of by the most valuable companies in Silicon Valley, the most powerful governmental agencies, and the most influential social movements. What they have in common is that they use computational tools to understand, and ultimately influence human behavior and social dynamics. An increasing part of human interaction leaves a massive digital footprint behind. Studying it allows us to gain unprecedented insights into what society is and how it works, including its intricate social networks that had long been obscure. Computational power allows us to detect hidden patterns through analytical tools like machine learning and to natural language processing. Finally, computer simulations enable us to explore hypothetical situations that may not even exist in reality, but that we would like to exist: a better world. This specialization serves as a multidisciplinary, multi-perspective, and multi-method guide on how to better understand society and human behavior with modern research tools. This specialization gives you easy access to some of the exciting new possibilities of how to study society and human behavior. It is the first online specialization collectively taught by Professors from all 10 University of California campuses....
Computational Social Science

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, 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. Learn more.

  • These are some reflections shared by students who have worked through the content of the Specialization on Computational Social Science:

    • "Highly enjoyable and most importantly, giving me exceptionally important skills to fulfill my job requirements at a new position in Munich. You may be interested to know the impact of your course on salary and in my case, the knowledge and certification gained adds about another Euro 20.000 on the annual salary (taking it to about Euro 120.000 p.a.)."
    • "My overall impression of this was: I can't wait to use this for other stuff!!"
    • "I absolutely think that these tools could be used in my future jobs, or even as a personal reflection. If you scrape and analyze the comments/reactions that your business gets on Youtube, Twitter, Instagram, etc., what does their language use say about how they interact with your brand — or what your brand brings out in them?"
    • "Wow, this is cool and fun stuff. Even though I may not pursue anything social-science related in the near future, it is still nice to learn and get to experience all of these tools that computational social science offers and benefits in all kinds of careers and fields of study."
    • "I particularly enjoyed the web-scraping for some reason. It feels very advanced although its very easy. ...It seems to be a very fast and efficient way of grabbing data."
    • "I enjoyed playing around with machine learning! ...It was also amazing to me how quickly it was able to grasp and learn our input in seconds. It makes me wonder how much more technology will advance in these next few years... It's scary but fascinating."
    • "The fact that these tools are so easily usable and attainable is incredible in my mind. Not only do we have access to them like we have access to things like Facebook and Twitter, but they're FREE."
    • "The most interesting aspect was the fact that these tools are all free and online. In the past, only researchers at well-funded universities had access to programs like the ones we used in all of our labs. But now, even someone without much technical knowledge on complex software can use these tools."
    • "I am so surprised that these tools are available to anyone through a simple download, and even more so that they are very user friendly and easy to learn how to navigate. I plan on starting a clothing line company in the future and I think it will be really helpful for me to be able to analyze so much online data."
    • "As an Environmental Policy Analysis and Planning major, I was fascinated to learn that there is a feasible way to simulate policy implementation and impact multiple times within a short span of time."
    • "UCCSS has allowed me to feel more confident in my abilities with a computer and to better understand companies like Facebook or Twitter. ...these tools really are powerful but also dangerous. ...It allows powerful individuals to manipulate ideas."
    • "Throughout the course, the content was challenging, but when it was finally applied to the labs at the end of each module, it was really rewarding to see everything play out. It was even more rewarding when it made sense too! ... I'm really glad I took this course! It was definitely a challenge, but I'm glad I got to experience and learn about so many topics I never knew even existed."
    • "It was fun seeing the results of the code that I made, and I never thought that I would be doing something like this in my life. The results also showed me what the society would look like.... Social network analysis and web scraping could be the tools that I use in my future job as all the internship that I'm looking now all related to social media or digital media."
    • "My career aspiration is to be a digital marketing expert. These computational tools have enormous implications for the field."
    • "I really really loved that this class let me learn hands-on and gave me experience with tools that have real world application and combine STEM & social science. I think that a lot of these tools are useful far beyond homework activities."
    • "Best course I have taken. I wish more online courses structured like this would be offered."
  • This Specialization on Computational Social Science is the result of a collective effort with contributions from Professors from all 10 campuses of the University of California. It is coordinated by Martin Hilbert, from UC Davis, and counts with lectures from:

    1) UC Berkeley: Joshua Blumenstock, Prof. iSchool; Stuart Russell, Professor of Computer Science and Engineering.

    2) UC Davis: Martin Hilbert, Prof., Dpt. of Communication & Seth Frey, Prof., Dpt. of Communication & Cynthia Gates, Director of the IRB.

    3) UC Irvine: Lisa Pearl, Prof. Cognitive Sciences.

    4) UC Los Angeles: PJ Lamberson, Assistant Prof. Communication Studies.

    5) UC Merced: Paul Smaldino, Prof. Cognitive and Information Sciences.

    6) UC Riverside: Christian Shelton, Prof. Computer Science.

    7) UC San Diego: James Fowler, Prof. Global Public Health and Political Science.

    8) UC San Francisco: Maria Glymour, Associate Prof. School of Medicine, Social Epidemiology & Biostatistics.

    9) UC Santa Barbara: René Weber, Prof. Dpt. of Communication & Media Neuroscience Lab (with Frederic Hopp).

    10) UC Santa Cruz: Marilyn Walker, Prof. Computer Science, Director, Computational Media.

  • This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

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