vcc.ca
CSTP 2130: AI Technologies
Effective date
September 2026
Department
Computer Systems Tech Diploma
School
Trades, Technology and Design
Description
Students learn new and emerging artificial intelligence (AI) technologies. These technologies are disruptive and are creating new streams of functionalities, apps, and products. Students examine trends, changes in software development practices, and application development directions. They apply Machine Learning (ML) techniques in data analysis and embed AI agents in software applications. The course also reviews AI applications in Cloud computing, virtualization, system simulation, and network security.
Credits
3.0
Year of study
2nd Year Post-secondary
Prerequisites
CSTP 1130 or equivalent, taken prior to or concurrently; CSTP 1150 or equivalent, taken prior to or concurrently.
Corequisites
None
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
- Identify emerging technologies that are changing the marketplace
- Explain the key concepts of machine learning and data analysis
- Explain the key concepts of Generative AI (gen AI) and large language models (LLMs)
- Explain the key concepts of AI agents
- Identify the processes required to implement emerging technologies, with a focus on integrating AI into existing systems
- Develop plans for introducing a new AI technology in simulated workplace setting
- Apply AI techniques to develop innovative solutions and applications
- Apply AI techniques in software development.
- Add AI capabilities to existing software applications
Prior Learning Assessment & Recognition (PLAR)
None
Hours
Lecture, Online, Seminar, Tutorial: 30
Clinical, Lab, Rehearsal, Shop, Kitchen, Simulation, Studio: 30
Total Hours: 60
Clinical, Lab, Rehearsal, Shop, Kitchen, Simulation, Studio: 30
Total Hours: 60
Instructional Strategies
Instructional strategies include classroom lectures, demonstrations, group discussions, computer labs and hands-on practical work.
Grading System
Letter Grade (A-F)
Passing grade
C
Evaluation Plan
|
Type |
Percentage |
Assessment activity |
|
Assignments |
40 |
|
|
Midterm Exam |
20 |
In-class written exam. |
|
Project |
20 |
Team project. |
|
Final Exam |
20 |
In-class written exam. |
Course topics
- The dynamics of emerging AI technologies
- foundations of machine learning and techniques
- Data collection and preparation for machine learning applications
- AI libraries and tools
- Algorithms for regression, classification, reinforcement learning
- Development of software applications with AI capabilities
- Projects with real-world applications
Notes:
- Course contents and descriptions, offerings and schedules are subject to change without notice.
- Students are required to follow all College policies including ones that govern their educational experience at VCC. Policies are available on the VCC website at:
https://www.vcc.ca/about/governance--policies/policies/. - To find out if there are existing transfer agreements for this course, visit the BC Transfer Guide at https://www.bctransferguide.ca.