Intro to AI & Machine Learning
In this course, we will demystify Artificial Intelligence and Machine Learning through the lens of building and deploying AI systems responsibly. We will start by understanding what AI really is and then discuss what responsibility means in the AI context.
- Module 1: Introduction to Artificial Intelligence
- Module 2: What is Machine Learning?
- Module 3: Components of Machine Learning System
- Module 4: Traditional Software vs Machine Learning
- Module 5: Machine Learning Tasks
- Module 6: The Machine Learning Experience
- Module 7: Training, Optimization and Generalization
- Module 8: Underfitting, Overfitting and Regularization
- Module 9: Self-regulation and Machine Learning as a Dual-use Technology
- Module 10: Recap of AI Course & Explainable AI
- Final Quiz
Prof. Graham Taylor, PhD, P.Eng.
- Canada CIFAR AI Chair
- Associate Professor of Engineering, University of Guelph
- Academic Co-director of University of Guelph Centre for Advancing Responsible and Ethical AI (CARE-AI)
- Member of the Vector Institute for AI
- Co-organizer of the annual CIFAR Deep Learning Summer School
- Instructor to more than 70 students and researchers on AI-related projects.
- One of 18 inaugural CIFAR Azrieli Global Scholars
- One of Canada's Top 40 under 40
Visiting Faculty member at Google Brain
- Co-founder of Kindred, which was featured at number 29 on MIT Technology Review's 2017 list of smartest companies in the world
- Academic Director of NextAI, a non-profit accelerator for AI-focused entrepreneurs
This Intro to AI & Machine Learning Course is part of the Skills4Good Responsible AI Program.