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URL: https://www.coursera.org/learn/responsible-ai-for-developers-fairness--bias

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Responsible AI for Developers: Fairness & Bias

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Responsible AI for Developers: Fairness & Bias

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Gain insight into a topic and learn the fundamentals.
4.7

18 reviews

Intermediate level
Some related experience required
3 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.7

18 reviews

Intermediate level
Some related experience required
3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Define what is Responsible AI

  • Identify Google’s AI principles

  • Describe what AI fairness and bias mean

  • Explain how to identify and mitigate biases through data and modeling

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

2 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Responsible AI for Developers Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.

This module introduces the course structure and objectives.

What's included

1 video

1 video•Total 1 minute
  • Course Introduction•1 minute

This module provides an overview of Responsible AI, covering Google’s AI Principles and sub-topics of Responsible AI. Also, this provides actual case studies of Responsible AI in Google products.

What's included

4 videos1 assignment

4 videos•Total 24 minutes
  • AI & Responsibility•6 minutes
  • Google’s AI Principles•5 minutes
  • Responsible AI Practices•8 minutes
  • Case study: Google Flights•6 minutes
1 assignment•Total 8 minutes
  • Quiz 1 •8 minutes

This module focuses on AI Fairness and Bias. It provides various techniques and tools to identify and mitigate biases through data and modeling.

What's included

8 videos1 assignment1 app item1 plugin

8 videos•Total 37 minutes
  • Overview of Fairness and Bias•8 minutes
  • Identify Bias - TFDV Tool•5 minutes
  • Identify Bias - What-if Tool•4 minutes
  • Identify Bias - TFMA Tool•2 minutes
  • Mitigate Bias - Data Intervention•7 minutes
  • Mitigate Bias - Threshold Calibration•5 minutes
  • Mitigate Bias - Model Remediation•5 minutes
  • Lab: Mitigate Bias with MinDiff in TensorFlow•1 minute
1 assignment•Total 6 minutes
  • Quiz 2•6 minutes
1 app item•Total 90 minutes
  • Lab: Mitigate Bias with MinDiff in TensorFlow•90 minutes
1 plugin•Total 15 minutes
  • Accessing and completing labs•15 minutes

This module provides a summary of the entire course by covering the most important concepts, tools, and technologies.

What's included

1 video1 reading

1 video•Total 2 minutes
  • Course Summary•2 minutes
1 reading•Total 10 minutes
  • Reading•10 minutes

Student PDF links to all modules

What's included

1 reading

1 reading•Total 10 minutes
  • Course Resources•10 minutes

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Instructor

Google Cloud
2,244 Courses•4,416,115 learners

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Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,