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Big Data, Artificial Intelligence, and Ethics Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
1 days
Duration
1 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
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Taught in
English
Taught in
English

About

This Big Data, Artificial Intelligence, and Ethics course offered by Coursera in partnership with UC Davis gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. 

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.

Programme Structure

Course structure:

  • Big Data Limitations
  • Footprint ≠ Representativeness
  • Data ≠ Reality
  • Meaning ≠ Meaningful
  • Discrimination ≠ Personalization
  • Correlation ≠ Causation

Key information

Duration

  • Part-time
    • 1 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

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

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • 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.

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