This course gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. With more than 99% of all mediated information in digital format and with 98% of the world population using digital technology, humanity produces an impressive digital footprint. In theory, this provides unprecedented opportunities to understand and shape society. In practice, the only way this information deluge can be processed is through using the same digital technologies that produced it. Data is the fuel, but machine learning it the motor to extract remarkable new knowledge from vasts amounts of data. Since an important part of this data is about ourselves, using algorithms in order to learn more about ourselves naturally leads to ethical questions. Therefore, we cannot finish this course without also talking about research ethics and about some of the old and new lines computational social scientists have to keep in mind. As hands-on labs, you will use IBM Watson’s artificial intelligence to extract the personality of people from their digital text traces, and you will experience the power and limitations of machine learning by teaching two teachable machines from Google yourself.
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このコースについて
学習内容
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.
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カリフォルニア大学デービス校(University of California, Davis)
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
シラバス - 本コースの学習内容
Getting Started and Big Data Opportunities
In this module, you will be able to define the idea of big data and digital footprint. You will be able to discuss how big data is represented in social science and identify the opportunities of big data.
Big Data Limitations
In this module, you will be able to explain the limitations of big data. You will work with an AI interface, IBM Watson, and discover how AI can identify personality through Natural Language Processing. You will analyze the personality of a person.
Artificial Intelligence
In this module, you will discover the history of artificial intelligence (AI) and its fields of study. You'll be able to examine how AI is used through case studies. You will be able to discuss the application of AI and you will use AI to create a unique artifact through a hands-on exercise.
Research Ethics
In this module, you will be able to define the term research ethics. You will be able to examine the role ethics plays in conducting research. You will be able to discuss how ethics is applied when using AI and big data.
レビュー
- 5 stars71.54%
- 4 stars22.60%
- 3 stars4.25%
- 2 stars0.79%
- 1 star0.79%
BIG DATA, ARTIFICIAL INTELLIGENCE, AND ETHICS からの人気レビュー
Excellent course. Professon Martin Hilbert has done an excellent jon in terms of content, presentation as well as explanation. Thank you.
The course gave me absolutely great insights into AI & Big Data. Will definitely carry forward the discipline and will engage in an advanced level course.
I really enjoyed Martin's presentation style and his clear enthusiasm and knowledge about the topic, thank you.
Excellent course on How the Big Data, AI and ML technology plays a big role in developing the world. Thanks to all the professors who made it even easier to understand the subject with clarity.
計算社会科学専門講座について
For more information please view the Computational Social Science Trailer

よくある質問
いつ講座や課題にアクセスできるようになりますか?
この専門講座をサブスクライブすると何を行うことができるようになりますか?
学資援助はありますか?
What do students say after completion?
Since this Specialization is a collective effort from all UC campuses, who teaches it?
さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。