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Voltar para Big Data, Artificial Intelligence, and Ethics

Comentários e feedback de alunos de Big Data, Artificial Intelligence, and Ethics da instituição Universidade da Califórnia, Davis

405 classificações

Sobre o curso

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....

Melhores avaliações


27 de abr de 2020

A perfect course for beginners and non-computational professionals who are curious to explore Digital foot print, the state of the art Artificial Intelligence applications and the research ethics.


8 de jul de 2020

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.

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1 — 25 de 107 Avaliações para o Big Data, Artificial Intelligence, and Ethics


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por Charlotte H

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5 de nov de 2021

por Peter H

30 de jul de 2022