This hands-on entry level course provides an overview of Artificial Intelligence (AI) and is offered by BCIT Computing Part-time Studies. There are no specific prerequisites other than being proficient in using a personal computer, and being able to interact and communicate with others on a group project. Aimed at business or IT professionals and other who are curious about learning AI fundamentals, students begin by discussing AI concepts, and making comparisons to Machine Learning (ML) and Data Science. Lectures combined with labs and exercises focus using AI solutions. COMP 1021 was developed as part Canada's Digital Technology Supercluster capacity building project Athena Pathways. It is designed to help more Canadian women see the potential of the tech sector, and how a career in AI aligns with their skills and interests. Topics include; supervised learning, neural networks, unsupervised learning, and reinforcement learning. Commonly used AI tools and platforms allow participants to prepare data, train and evaluate their models. Online discussions include: natural language processing and decision making, as well as social issues and implications due to the limitations of AI. COMP 1021 is an elective in the Applied Information Systems (ACIS) Associate Certificate, which is a sub-set of the Computer Systems Technology (CST) Diploma. Please Note: COMP 1021 only counts for credit in ACIS and is not available to international students. Evaluation includes significant participation, labs, activities, online quizzes, group work and a project presentation. Upon successful completion students will be able to develop and deploy a no-code AI solution using Microsoft Azure.
(Grade 12 English and COMP 1002) or equivalent.
Below is one offering of this course for the Winter 2021 term.
Sat Jan 09 - Sat Apr 10 12 Weeks
|Jan 09 - Apr 10||Sat||09:00 - 12:00||
See Notes below
Upon successful compleltion of this course, the student will be able to:
Effective as of Fall 2020
COMP 1021 is offered as a part of the following programs:
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