EdX

Bias and Discrimination in AI (edX)

Offered by Université de Montréal, UMontrealX,
Bias and Discrimination in AI (edX)

Discover how even computer algorithms may be biased and have a serious impact on our every day lives. In this MOOC, based on an IVADO School involving various international experts in the field, you will learn how to identify and alleviate bias and discrimination in Artificial Intelligence.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Engage in this course pertaining to a highly impactful yet, too rarely discussed, AI-related topic. You will learn from international experts in the field, also speakers at IVADO’s International School on Bias and Discrimination in AI, which took place in Montreal, and explore the social and technical aspects of bias, discrimination and fairness in machine learning and algorithm design.
The main focus of this course is: gender, race and socioeconomic-based bias as well as bias in data-driven predictive models leading to decisions. The course is primarily intended for professionals and academics with basic knowledge in mathematics and programming, but the rich content will be of great use to whomever uses, or is interested in, AI in any other way. These sociotechnical topics have proven to be great eye-openers for technical professionals!
The total duration of the video content available in this course is 7:30 hours, cut into relevant segments that you may watch at your own pace. There are also comprehensive quizzes at the end of each segment to measure your understanding of the content.
IVADO is a scientific and economic data science hub bridging industrial, academic and governmental partners with expertise in digital intelligence. One of its missions is to contribute to the advancement of digital knowledge and train new generations of bias-aware data scientists.
Welcome to this enlightening journey in the world of ethical AI!

What you'll learn

  • Understanding bias and discrimination in all its aspects
  • Exploring the harmful effects of bias in machine learning (discriminatory effects of algorithmic decision-making)
  • Identifying the sources of bias and discrimination in machine learning
  • Mitigating bias in machine learning (strategies for addressing bias)
  • Recommendations to guide the ethical development and evaluation of algorithms

Syllabus

Module 1 The concepts of bias and fairness in AI

  • Different Types of Bias
  • Fairness criteria and metrics

Module 2Fields where problems were diagnosed

  • Privacy, labour and legal system
  • Public policy and Health

Module 3Institutional attempts to mitigate bias and discrimination in AI

  • Canada's Algorithmic Impact Assessment Framework
  • The Montreal Declaration for Responsible AI

Module 4Technical attempts to mitigate bias and discrimination in AI

  • Fairness constraints in graph embeddings
  • Gender bias in text
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

PyTorch Basics for Machine Learning (edX) EdX
IBM

PyTorch Basics for Machine Learning (edX)

Statistics & Data Analysis Data Science

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

Self Paced
Self-Paced
ML Machine Learning Linear Regression
Details
Visualización de Datos y Storytelling (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Visualización de Datos y Storytelling (edX)

Engineering Statistics & Data Analysis

Aprende en este curso en línea que es la visualización de datos, sus usos; los elementos que la conforman y la forma de poder utilizarla para el apoyo en la toma de las mejores decisiones para las empresas basadas en el análisis de datos. Digamos que necesitas comprender big data; miles o incluso millones de filas de datos, y tienes poco tiempo para hacerlo. los datos pueden provenir de tu equipo, en cuyo caso tal vez ya estés familiarizado con lo que estás midiendo y de los resultados que se esperan. O puede provenir de otro equipo, o tal vez de varios equipos a la vez, y estar completamente familiarizado.

Self Paced
Self-Paced
Big Data Storytelling Data Science
Details
Probability and Statistics in Data Science using Python (edX) EdX
University of California, San Diego,UC San DiegoX

Probability and Statistics in Data Science using Python (edX)

Statistics & Data Analysis CS: Programming

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

Self Paced
Self-Paced
Programming Python Statistics
Details
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Statistics & Data Analysis Data Science

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Probability Machine Learning Regression
Details
Data Science and Agile Systems for Product Management (edX) EdX
University of Maryland, College Park,University System of Maryland - USM,USMx,UMD

Data Science and Agile Systems for Product Management (edX)

Management & Leadership CS: Design & Product

Deliver faster, higher quality, and fault-tolerant products regardless of industry using the latest in Agile, DevOps, and Data Science. Modern systems today must be designed for agility in order to outpace the competition. Concepts like Agile, DevOps, and Data Science were once considered only for the technology-based companies. Today that means every company. Because there is no greater currency than timely information for optimizing operations and meeting the needs of customers.

Self Paced
Self-Paced
Agile Data Science Product Management
Details
Introduction to Computer Science and Programming (edX) EdX
Tokyo Institute of Technology,TokyoTechX

Introduction to Computer Science and Programming (edX)

CS: Programming

The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simultation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to basics and key concepts of computer science. By following the lectures and exercises of this course you will have an understanding of algorithms and you will get a real experience of programming using the language Ruby.

Self Paced
Self-Paced
Programming Artificial Intelligence Big Data
Details
Computational Thinking and Big Data (edX) EdX
University of Adelaide,AdelaideX

Computational Thinking and Big Data (edX)

CS: Software Engineering Statistics & Data Analysis

Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets. Computational thinking is an invaluable skill that can be used across every industry, as it allows you to formulate a problem and express a solution in such a way that a computer can effectively carry it out.

Self Paced
Self-Paced
Big Data Data Science Algorithmic Thinking
Details
Big Data Capstone Project (edX) EdX
University of Adelaide,AdelaideX

Big Data Capstone Project (edX)

Statistics & Data Analysis Data Science

Further develop your knowledge of big data by applying the skills you have learned to a real-world data science project. This project will give you the opportunity to deepen your learning by giving you valuable experience in evaluating, selecting and applying relevant data science techniques, principles and theory to a data science problem. This project will see you plan and execute a reasonably substantial project and demonstrate autonomy, initiative and accountability.

Self Paced
Self-Paced
Big Data Data Science Data Analytics
Details