
Overview
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 Big Data, Artificial Intelligence, and Ethics course offered by Coursera in partnership with UC Davis 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.
What you'll 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.
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Visit programme websiteProgramme Structure
Course structure:
- Big Data Limitations
- Footprint ≠ Representativeness
- Data ≠ Reality
- Meaning ≠ Meaningful
- Discrimination ≠ Personalization
- Correlation ≠ Causation
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Data Science & Big Data Artificial Intelligence Ethics View 11 other Short Courses in Ethics in United StatesExplore more key information
Visit programme websiteWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Beginner level
- No previous experience necessary
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
- Audit: free access to course materials except graded items
- Certificate: a trusted way to showcase your skills
- A year of unlimited access with Coursera Plus $199
Funding
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.