Fairness in AI Courses and Certifications

Molecular Imaging & Therapy

Lack of Fairness in AI-Based Medical Image Diagnostic Tools

Explore fairness challenges in AI-based medical image diagnostics with Dr. Seyyed-Kalantari. Gain insights on developing responsible AI tools for trustworthy clinical deployment.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

Association for Computing Machinery (ACM)

The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa

Explore the intersection of AI, healthcare, and colonial impacts in Africa through a mixed-methods analysis examining fairness, ethical considerations, and technological implementation challenges.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

Introduction to Deep Learning

24 ratings

Deep Learning is subset of machine learning focused on extracting patterns from data using neural networks and use those patterns to inform the learning tasks.

• YouTube
• 2 days 7 hours 16 minutes
• Self-Paced
• Free Video

Responsible AI for Developers: Fairness & Bias

18 ratings at Coursera

Learn techniques to identify and mitigate fairness and bias issues in AI/ML practices using Google Cloud products and open-source tools, while implementing Responsible AI principles.

• Coursera
• 3 hours 22 minutes
• Self-Paced
• Paid Course

Lessons From Evaluating and Debugging Healthcare AI in Deployment

Explore challenges in translating AI to healthcare: data curation, model testing, and human-AI interactions. Learn insights from real-time AI trials and FDA-approved medical AI systems analysis.

• YouTube
• 57 minutes
• Self-Paced
• Free Video

Yannic Kilcher

Is the Problem in the Data? Examples on Fairness, Diversity, and Bias

Exploring AI bias through interactive examples on fairness, diversity, and hidden biases. Examines whether bias issues stem from data or other factors in machine learning models.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

Privacy, Bias, and Fairness in AI

Explore privacy concerns, bias detection, and fairness frameworks in AI systems while learning practical mitigation techniques for responsible algorithmic design.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Data, Algorithms, Justice and Fairness - Lecture 2

Exploring algorithmic fairness in justice systems: accuracy, data sources, and potential biases. Discusses AI decision-making, explainability, and societal implications of algorithms in criminal justice.

• YouTube
• 1 hour 34 minutes
• Self-Paced
• Free Video

Alan Turing Institute

Human-Compatible Artificial Intelligence - Stuart Russell, University of California

Stuart Russell explores the potential and risks of AI surpassing human capabilities, proposing a fundamental shift in AI development to ensure beneficial outcomes and addressing key ethical and philosophical questions.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Alan Turing Institute

Fairness and Robustness in Machine Learning – A Formal Methods Perspective - Aditya Nori, Microsoft

Explore fairness in machine learning through formal methods. Learn techniques for verifying probabilistic properties and certifying fairness in decision-making programs using FairSquare.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Association for Computing Machinery (ACM)

KDD TransFAT - Translating Fairness, Accountability, and Transparency - Julia Stoyanovich

Explore ethical AI challenges in automated decision systems, focusing on fairness, accountability, and transparency in hiring processes and beyond.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

PyCon US

AI with a Conscience: Building Fair and Transparent Systems in Python

Explore fairness in AI with Python's fairlearn library, learning to measure and mitigate biases in machine learning models through real-world examples and techniques like demographic parity and threshold optimization.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

AI Bias and Fairness

Comprehensive exploration of AI bias and fairness, covering types, sources, and mitigation strategies. Examines interpretation-driven and data-driven biases, feature bias, and advanced debiasing techniques for ethical AI development.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

AI Ethics

Explore AI ethics focusing on principles, fairness, bias reduction, and trust in AI design.

• DataCamp
• 1 hour
• Self-Paced
• Free Trial Available

Simons Institute

Privacy and Fairness in Collaborative AI

Explore information-theoretic approaches to enhance privacy and fairness in collaborative AI systems, focusing on trustworthy machine learning techniques.

• YouTube
• 33 minutes
• Self-Paced
• Free Video