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.
This course is part of the Computational Social Science Specialization
About this Course
What you will learn
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.
Syllabus - What you will learn from this course
Getting Started and Big Data Opportunities
Big Data Limitations
- 5 stars72.12%
- 4 stars21.76%
- 3 stars4.40%
- 2 stars0.73%
- 1 star0.97%
TOP REVIEWS FROM BIG DATA, ARTIFICIAL INTELLIGENCE, AND ETHICS
It was a great experience learning a new language ;) . This course gives a lot info regarding big data ,its applications and IBM (I loved nature learning processing ).
I really enjoyed Martin's presentation style and his clear enthusiasm and knowledge about the topic, thank you.
Overall, good and informative content. Production quality and supplemental materials could be improved upon, however. Also, some quizzes are not always clear...
Excellent course, lots of interesting concepts covering the field of artificial intelligence and a welcomed take on research ethics.
About the Computational Social Science Specialization
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