UBC Engineering’s world-class faculty and researchers are committed to an instructional approach that is varied, experiential and engaging. This multi-faceted approach makes UBC engineers stand apart, on a firm foundation from which to build an exciting and rewarding career.
What you might expect/course format
While each course varies based on the subject and instructor, our VSP Packages feature:
- Interactive in person lectures
- Hands-on labs, fun and practical demonstrations
- Team-based assignments
- Fun social activities
- Tours of industrial facilities (some programs)
- Experience with industry standard software
July 2026 Course Packages
*April 15, 2025: This course package has been redesigned to further enhance the academic experience. The updated course package descriptions are provided below. Applicants to the previous version have been notified of the available options.
More than half of all code on GitHub is now written with AI assistance. Nearly a quarter of enterprise code is AI-generated. The developers who thrive in this landscape are not the ones who memorize syntax—they are the ones who know how to collaborate with AI to build real software, faster and more reliably than ever before.
Through two aligned courses, you will learn the concepts behind AI-augmented development
and apply them to a real team project every afternoon. In a few weeks, your team will have designed, built, tested, secured, and deployed a full-stack web application.
AI-Augmented Software Development
Concepts, techniques, and tools for building software with AI coding agents. Each morning session introduces a new capability—from prompting and context engineering to agent architecture, security, and ethics.
AI-Augmented Software Engineering Studio
A project-based course in software engineering. Each afternoon opens with a focused SE workshop, then your team applies both the morning’s AI concepts and the afternoon’s engineering practices to build a real application.
Prerequisites: No prerequisites
Introduction to Digital Signal/Image Processing
This introductory course focuses on basic concepts and tools of digital signal and image processing. It introduces basic digital signal & image processing theory in the context of real-world applications. Major topics of interest include: Fourier transform, digital filter, correlation, image basics, image filtering, extension to image and video processing applications. Students will explore the basics of signal and image processing and gain the hands-on experience (e.g., using MATLAB and OpenCV software) with project assignments.
Introduction to Hands-on Deep Learning with Python
This introductory course introduces basic concepts and core fundamentals of Deep Learning. Students will learn representative model types, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs), and their suitability for different learning tasks, through a set of hands-on examples. Each day’s class comprises two parts: a lecture part, which introduces the theory/method and use intuitive/prototype example(s) to illustrate the major concepts, and a hands-on learning part that students work on a specific real-world example. All examples are implemented in Python. By the end of this course, students will finish a term project through designing, developing and implementing a real-world application using open codes, toolbox and software (e.g., standard API calls and AI platforms).
Prerequisites: Basic programming skills (e.g., Matlab, Python); Math foundation (Probability & statistics, Calculus)
For more information
For VSP Electrical and Computer Engineering-specific questions, please email vsp@ece.ubc.ca.
Student testimonials
– Zhaolin Shu, VSP Applied Science Student
– Ducheng Lu, VSP Applied Science Student