Monthly Subscription Starting at AED 99 + VAT

Artificial Intelligence Data Fairness and Bias
  • Level Foundation
  • المدة 7 ساعات hours
  • الطبع بواسطة LearnQuest
  • Offered by

عن

In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.

الوحدات

Introduction to the course

    • 1 Videos
    • 1 Discussion
Show info about module content

1 Discussions

  • Course welcome

1 Videos

  • Course Introduction Video

What is algorithmic fairness?

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Knowledge Check

2 Videos

  • Model parity: a balancing act
  • Protecting groups, protecting individuals

1 Readings

  • The Equality Conundrum

Fairness vs accuracy

    • 2 Videos
    • 1 Readings
    • 1 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Knowledge Check
  • Weekly Quiz

1 Discussions

  • COMPAS and fairness

2 Videos

  • Imperfect modeling
  • Weekly Review

1 Readings

  • COMPAS article

Fairness as an algorithm

    • 2 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Knowledge Check

2 Videos

  • Algorithms inside of algorithms: Getting to fair
  • Testing in theory: fair loan decisions

Deploying Fairness: combating bias in practice

    • 3 Videos
    • 2 Readings
    • 1 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Knowledge Check
  • Weekly Quiz

1 Discussions

  • Getting to fair

3 Videos

  • Deploying fairness: combating bias in practice
  • Adversarial Models: Word2Vec
  • Weekly Review

2 Readings

  • Unfairness visualized
  • Research Paper: Debiasing Word Embeddings

Human factors: bias

    • 2 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Knowledge Check

2 Videos

  • Getting out of your head: bias awareness
  • Building an exploratory training set

1 Readings

  • Full list of cognitive biases

Models under the influence

    • 3 Videos
    • 1 Readings
    • 1 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Knowledge Check
  • Weekly Quiz

1 Discussions

  • Future bias

3 Videos

  • Imperfect modeling: finding a balance
  • Human Factors: Game Theory
  • Weekly Review

1 Readings

  • Monster Match

Auto Summary

Discover the critical aspects of fairness and bias in machine learning with the "Artificial Intelligence Data Fairness and Bias" course, designed for data science and AI enthusiasts. Guided by expert instructors on Coursera, this foundational course delves into the ethical considerations essential for creating equitable predictive models. Over the course of 420 minutes, you will learn to identify and mitigate human biases and improve dataset awareness to ensure fair decision-making in applications ranging from college admissions to loan approvals. Accessible through Starter and Professional subscription plans, this course is ideal for those eager to build more ethical AI systems and make a meaningful impact in the field of data science.

Brent Summers
Instructor

Brent Summers