Various education programs and courses at UBC focus on machine learning and its applications. This is a non-exhaustive list. You can click on each course for additional information, and to see if the course is delivered during the current semester.
Educational Programs
Please follow the links below for information on educational programs at UBC with a major focus on machine learning:
- Bachelor of Science in Computer Science
- MSc in Computer Science
- Master of Data Science
- PhD Track MSc. Program
- PhD in Computer Science
Machine Learning Courses
Problem-solving and planning; state/action models and graph searching. Natural language understanding Computational vision. Applications of artificial intelligence.
Winter 2023CPSC322 Introduction to Artificial Intelligence Sections
Problem-solving and planning; state/action models and graph searching. Natural language understanding Computational vision. Applications of artificial intelligence.
Application of machine learning tools, with an emphasis on solving practical problems. Data cleaning, feature extraction, supervised and unsupervised machine learning, reproducible workflows, and communicating results.
Winter 2023No CPSC course(s) were found for W2023 term.
We introduce basic principles and techniques in the fields of data mining and machine learning. These are some of the key tools behind the emerging field of data science and the popularity of the `big data’ buzzword. These techniques are now running behind the scenes to discover patterns and make predictions in various applications in our daily lives. We’ll focus on many of the core data mining and machine learning technlogies, with motivating applications from a variety of disciplines.
Winter 2023CPSC340 Machine Learning and Data Mining Sections
Models of algorithms for dimensionality reduction, nonlinear regression, classification, clustering and unsupervised learning; applications to computer graphics, computer games, bio-informatics, information retrieval, e-commerce, databases, computer vision and artificial intelligence.
Principles and techniques underlying the design, implementation and evaluation of intelligent computational systems. Applications of artificial intelligence to natural language understanding, image understanding and computer-based expert and advisor systems. Advanced symbolic programming methodology.
Winter 2023CPSC422 Intelligent Systems Sections
Principles and techniques underlying the design, implementation and evaluation of intelligent computational systems. Applications of artificial intelligence to natural language understanding, image understanding and computer-based expert and advisor systems. Advanced symbolic programming methodology.
Introduction to the processing and interpretation of images. Image sensing, sampling, and filtering. Algorithms for colour analysis, texture description, stereo imaging, motion interpretation, 3D shape recovery, and recognition.
Winter 2023CPSC425 Computer Vision Sections
Introduction to the processing and interpretation of images. Image sensing, sampling, and filtering. Algorithms for colour analysis, texture description, stereo imaging, motion interpretation, 3D shape recovery, and recognition.
Advanced machine learning techniques focusing on probabilistic models. Deep learning and differentiable programming, exponential families and Bayesian inference, probabilistic graphical models and other generative models, Monte Carlo and variational inference methods.
Winter 2023CPSC440 Advanced Machine Learning Sections
Advanced machine learning techniques focusing on probabilistic models. Deep learning and differentiable programming, exponential families and Bayesian inference, probabilistic graphical models and other generative models, Monte Carlo and variational inference methods.
Artificial intelligence, machine learning techniques, Deep learning, Python libraries for machine learning, Basic signal processing techniques, Data Acquisition, Applications in Manufacturing, Use of sound to evaluate operation of CNC machinery, Use of AE sensor to evaluate metal 3D printing.
Winter 2023MANU465 AI and Machine Learning Applications in Manufacturing Sections
Artificial intelligence, machine learning techniques, Deep learning, Python libraries for machine learning, Basic signal processing techniques, Data Acquisition, Applications in Manufacturing, Use of sound to evaluate operation of CNC machinery, Use of AE sensor to evaluate metal 3D printing
No CPSC course(s) were found for W2023 term.
No CPSC course(s) were found for W2023 term.
This course is about learning to control the movement of humans, animals, and robots, with application to character animation, computer vision, robotics, and biological motor control. Much of the course will focus on (deep) reinforcement learning, which has seen many advances over the past 5 years.
Topics include kinematic and dynamic models of motion, basics of physics-based simulation, classical control methods, dynamic programming, and deep reinforcement learning. Background material will be introduced as necessary. Prior experience in computer graphics, robotics, introductory reinforcement learning, and deep learning will be helpful, but is not necessary.
Winter 2023No CPSC course(s) were found for W2023 term.
No CPSC course(s) were found for W2023 term.
This is an graduate (or senior undergraduate) course on machine learning, a field that focuses on using automated data analysis for tasks like pattern recognition and prediction. The course will move quickly and assumes a strong background in math and computer science as well as previous experience with statistics and/or machine learning. The class is intended as a continuation of CPSC 340/532M and it is strongly recommended that you take CPSC 340/532M first before enrolling in CPSC 540. Topics will (roughly) include deep learning, Markov models, latent-variable models, probabilistic graphical models, and Bayesian methods.
Winter 2023CPSC540 Machine Learning Sections