课程信息

86,156 次近期查看
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
第 2 门课程(共 5 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为11 小时
英语(English)
字幕:英语(English)

您将学到的内容有

  • Define and discuss big data opportunities and limitations.

  • Work with IBM Watson and analyze a personality through Natural Language Programming (NLP).

  • Examine how AI is used through case studies.

  • Examine and discuss the roles ethics play in AI and big data.

可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
第 2 门课程(共 5 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为11 小时
英语(English)
字幕:英语(English)

提供方

加州大学戴维斯分校 徽标

加州大学戴维斯分校

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 3 小时

Getting Started and Big Data Opportunities

完成时间为 3 小时
10 个视频 (总计 94 分钟), 3 个阅读材料, 1 个测验
10 个视频
Course Introduction6分钟
Big Data Overview2分钟
What is "Big Data"?14分钟
Digital Footprint5分钟
Political Data-fusion and No-Sampling (Part 1)14分钟
Political Data-fusion and No-Sampling (Part 2)3分钟
Real-time11分钟
Machine Learning5分钟
Machine Learning Recommender Systems11分钟
3 个阅读材料
About UCCSS10分钟
A Note From UC Davis10分钟
Optional/Complementary10分钟
1 个练习
Module 1 Quiz30分钟
2

2

完成时间为 3 小时

Big Data Limitations

完成时间为 3 小时
8 个视频 (总计 52 分钟), 1 个阅读材料, 3 个测验
8 个视频
Big Data Limitations2分钟
Footprint ≠ Representativeness10分钟
Data ≠ Reality6分钟
Meaning ≠ Meaningful4分钟
Discrimination ≠ Personalization8分钟
Correlation ≠ Causation6分钟
Past ≠ Future10分钟
1 个阅读材料
Welcome to Peer Review Assignments!10分钟
2 个练习
Natural Language Processing (NLP) Assignment Task5分钟
Module 2 Quiz30分钟
3

3

完成时间为 3 小时

Artificial Intelligence

完成时间为 3 小时
15 个视频 (总计 105 分钟), 1 个阅读材料, 1 个测验
15 个视频
A Short History of AI9分钟
State of the Art5分钟
The Most Intelligent Gamer4分钟
Search and Robotics7分钟
Vision and Machine Learning6分钟
AI Challenges3分钟
Moral Frames7分钟
Predictions From Morals6分钟
Moral Brain Signatures6分钟
Computational fMRI11分钟
(A Personal) History of Dialogue Systems6分钟
The Art of Dialogue10分钟
Making Conversations10分钟
AI Telling Stories7分钟
1 个阅读材料
Optional/Complementary10分钟
1 个练习
Module 3 Quiz30分钟
4

4

完成时间为 2 小时

Research Ethics

完成时间为 2 小时
13 个视频 (总计 105 分钟), 1 个阅读材料, 1 个测验
13 个视频
Origins: Unethical Medical Research8分钟
Unethical Social Research10分钟
Taking Responsibility12分钟
The Common Rule8分钟
Ethical Computational Social Science10分钟
Concerns of an AI Pioneer5分钟
Walker on Ethics10分钟
Shelton on Ethics7分钟
Language Acquisition (Complementary)6分钟
Modeling Framework (Complementary)9分钟
Computational Model (Complementary)6分钟
Lessons Learned (Complementary)6分钟
1 个阅读材料
Slaughterbots10分钟
1 个练习
Module 4 Quiz30分钟

审阅

来自BIG DATA, ARTIFICIAL INTELLIGENCE, AND ETHICS的热门评论

查看所有评论

关于 Computational Social Science 专项课程

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

常见问题

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

  • 如果订阅,您可以获得 7 天免费试听,在此期间,您可以取消课程,无需支付任何罚金。在此之后,我们不会退款,但您可以随时取消订阅。请阅读我们完整的退款政策

  • 是的,Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请,申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤,包括毕业项目。了解更多

  • These are some of the 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!!"
    • "Best course I have taken. I wish more online courses structured like this would be offered."
    • "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."
    • "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 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."
    • "I did my MA in Social Work in India. I am trying to make a come-back in my field after a long career break. I had been hearing Big Data and Data Science everywhere and wondered if there is a link between these and Social Sciences. This specialization gave me needed answers and is helping me to gain very useful skills... Thank you so much for bringing this specialization. You are a very good instructor and made these courses are a smooth sail."
  • 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.

  • 此课程不提供大学学分,但部分大学可能会选择接受课程证书作为学分。查看您的合作院校,了解详情。Coursera 上的在线学位Mastertrack™ 证书提供获得大学学分的机会。

还有其他问题吗?请访问 学生帮助中心