From foundational concepts to advanced applications, explore diverse artificial intelligence courses designed for learners at every stage. Choose from online, hybrid, and in-person formats taught by industry experts and academic leaders.
Filter courses by delivery method, skill level, and subject area to find the perfect fit for your learning journey.
Duration: 6 weeks • Self-paced
Provider: University of Toronto Extension
Topics: AI fundamentals, supervised learning, neural networks basics
Explore the foundational concepts of artificial intelligence including problem-solving techniques, knowledge representation, and search algorithms. This course provides an accessible entry point for individuals with minimal programming experience.
Prerequisites: Basic mathematics, logical thinking
Certificate: Digital certificate upon completion
Duration: 8 weeks • 10 hours/week
Provider: McGill University Professional Development
Topics: Regression, classification, clustering, model evaluation
Comprehensive introduction to machine learning algorithms and their practical applications. Students work with Python and scikit-learn to build predictive models, understand bias-variance tradeoffs, and implement validation strategies.
Prerequisites: Python programming, linear algebra, statistics
Certificate: Professional Certificate in Machine Learning
Duration: 12 weeks • Saturdays 9am-4pm
Provider: University of British Columbia Extended Learning
Topics: CNNs, RNNs, GANs, transformers, attention mechanisms
Advanced exploration of deep neural network architectures. Participants implement state-of-the-art models for computer vision, natural language processing, and generative tasks using TensorFlow and PyTorch frameworks.
Prerequisites: Machine learning experience, calculus, Python
Certificate: Advanced Certificate in Deep Learning
Duration: 10 weeks • Online + 4 in-person labs
Provider: University of Waterloo Continuing Education
Topics: Tokenization, embeddings, sentiment analysis, language models
Study techniques for processing and understanding human language computationally. Projects include building chatbots, text classifiers, and implementing pre-trained language models like BERT and GPT architectures.
Prerequisites: Python, basic ML knowledge, linguistics helpful
Certificate: Specialization Certificate in NLP
Duration: 8 weeks • Flexible schedule
Provider: Simon Fraser University Online
Topics: Data preprocessing, exploratory analysis, visualization, feature engineering
Learn essential data science skills required for AI applications. Master pandas, NumPy, and matplotlib while exploring datasets, identifying patterns, and preparing data for machine learning pipelines.
Prerequisites: Basic programming knowledge
Certificate: Foundation Certificate in Data Science
Duration: 10 weeks • Tuesdays & Thursdays 6-9pm
Provider: York University School of Continuing Studies
Topics: Image processing, object detection, segmentation, facial recognition
Develop expertise in computer vision techniques and applications. Implement convolutional neural networks for image classification, object detection with YOLO and Faster R-CNN, and semantic segmentation projects.
Prerequisites: Python, machine learning basics, linear algebra
Certificate: Certificate in Computer Vision Applications
Duration: 12 weeks • Weekly live sessions
Provider: University of Alberta Online Programs
Topics: MDPs, Q-learning, policy gradients, actor-critic methods
Master reinforcement learning algorithms for sequential decision-making problems. Implement agents for game playing, robotics control, and recommendation systems using OpenAI Gym and stable-baselines3 library.
Prerequisites: Strong programming, probability theory, ML experience
Certificate: Advanced Certificate in Reinforcement Learning
Duration: 6 weeks • Online + 2 weekend workshops
Provider: Ryerson University Chang School
Topics: Python syntax, data structures, NumPy, pandas, basic ML
Build strong Python programming foundations for AI development. Learn to manipulate data, create visualizations, and implement simple machine learning algorithms while following best coding practices.
Prerequisites: No programming experience required
Certificate: Python Programming for AI Certificate
Duration: 6 weeks • Asynchronous
Provider: University of Montreal Extension
Topics: Bias, fairness, privacy, transparency, accountability
Examine ethical considerations in AI development and deployment. Analyze case studies involving algorithmic bias, data privacy, and societal impacts. Learn frameworks for responsible AI design and implementation.
Prerequisites: Basic understanding of AI concepts
Certificate: Certificate in AI Ethics
Duration: 14 weeks • Wednesdays 6-9pm
Provider: University of Calgary Professional Faculties
Topics: Experimental design, paper writing, literature review, peer review
Develop skills for conducting original AI research. Learn to formulate research questions, design experiments, analyze results, and communicate findings through academic papers and conference presentations.
Prerequisites: Graduate-level AI knowledge, research interest
Certificate: Research Preparation Certificate
Duration: 8 weeks • Evening live sessions
Provider: Concordia University Professional Development
Topics: Model deployment, monitoring, CI/CD, containerization, cloud platforms
Learn to deploy and maintain machine learning models in production environments. Work with Docker, Kubernetes, AWS SageMaker, and MLflow to create scalable, monitored ML systems.
Prerequisites: ML experience, basic DevOps knowledge, cloud familiarity
Certificate: Professional Certificate in MLOps
Duration: 6 weeks • Online + community project
Provider: Dalhousie University Continuing Education
Topics: Healthcare AI, climate modeling, accessibility, humanitarian applications
Explore how artificial intelligence addresses societal challenges. Collaborate on projects related to healthcare diagnosis, environmental monitoring, disaster response, and accessibility technologies.
Prerequisites: Interest in social impact, basic technical literacy
Certificate: Certificate in AI for Social Impact
Real experiences from individuals who transformed their careers through AI education.
After 12 years teaching high school mathematics, Sarah enrolled in an online Machine Learning Foundations course. "The combination of asynchronous lectures and hands-on projects allowed me to learn while maintaining my teaching schedule," she explains. Within 18 months of completing her first course, Sarah transitioned to a machine learning engineer role at a Vancouver-based AI startup, working on predictive models for educational technology.
Courses Completed: Machine Learning Foundations, Deep Learning Specialization, MLOps & Deployment
Working as a hospital administrator, Marcus recognized the potential of AI in healthcare operations. He began with Data Science for AI, progressed through Computer Vision, and completed a capstone project analyzing medical imaging data. "The hybrid format was ideal - I could learn theory online and work with real equipment during in-person labs," he notes. Marcus now leads an AI initiatives team at his hospital, implementing predictive models for patient flow optimization.
Courses Completed: Data Science for AI, Computer Vision, AI Ethics & Governance
Emma, a member of the Haudenosaunee Confederacy, combined her linguistics background with AI training to preserve Indigenous languages. Through Natural Language Processing and AI for Social Good courses, she developed tools for Mohawk language learning. "The courses gave me technical skills, but more importantly, they taught me how to apply AI ethically and culturally appropriately," Emma reflects. She now collaborates with Indigenous communities across Canada on language revitalization projects.
Courses Completed: Natural Language Processing, AI for Social Good, Python for AI
Connect with our team to learn more about course options, prerequisites, and learning paths.