Topics in Computer Programming – Artificial Intelligence
|School||School of Computing and Academic Studies|
|Program||Bachelor of Technology - Computer Systems|
|Minimum Passing Grade||60%|
|Start Date||September 15, 2021|
|End Date||December 01, 2021|
|Pre-requisites||Acceptance into the Bachelor of Technology in Computer Systems Degree program OR special permission (COMP2121, MATH3042, COMP3522 or equivalent).|
Acknowledgement of Territories
The British Columbia Institute of Technology acknowledges that our campuses are located on the unceded traditional territories of the Coast Salish Nations of Sḵwx̱wú7mesh (Squamish), səl̓ilwətaɁɬ (Tsleil-Waututh), and xwməθkwəy̓əm (Musqueam).
|Name||Chi En Huang|
|Instructor to provide|
|Office Hours||Instructor to provide|
This course provides an introduction to the various topics in Artificial Intelligence (AI). Topics to be covered include search, games, regression, classification and neural networks. Students will develop an understanding of the fundamentals underpinning AI applications and gain hands-on experience through the development of AI systems. Practical work in course projects focuses on developing components of AI systems as well as analyzing real-world datasets from different domains. The societal implications and ethical considerations in the design of AI systems will also be discussed.
Course Learning Outcomes/Competencies
Upon successful completion of this course, the student will be able to:
- Describe current applications of AI.
- Solve problems using uninformed, informed and adversarial search techniques.
- Explain the concepts of learning and the differences between unsupervised, supervised and reinforcement learning.
- Explain the basics of different regression, classification and neural network techniques.
- Apply machine learning techniques and algorithms to datasets.
- Perform model selection and parameter tuning of machine learning techniques.
- Design and develop components of AI systems.
- Identify potential applications of AI techniques to real-world problems.
- Investigate societal implications and ethics of AI.
Artificial Intelligence: A Modern Approach (4th Edition)
Stuart Russell, Peter Norvig
The Elements of Statistical Learning (2nd Edition)
Trevor Hastie, Robert Tibshirani, Jerome Friedman
Note: Passing Grade is 60%.
Attendance in lectures and labs is mandatory.
In case of illness or other unavoidable cause of absence, the student must communicate as soon as possible with his/her instructor, indicating the reason for the absence.
Prolonged illness which causes the student to miss 10% or more of the lectures and labs will require a BCIT-approved medical certificate submitted to the department, substantiating the reason for the absence.
Unapproved absence of 10% or more of the lectures and labs may result in failure or forced withdrawal from this course.
Recording of lessons is prohibited without prior written consent of the instructor. If you wish to record lessons, you must contact the instructor during office hours and make suitable arrangements. In such cases where recordings are allowed by the instructor, these recordings are for the exclusive use of the student making the recording, and are not to be posted online or shared with others.
Course Schedule and Assignments
Solving Problems by Searching II
Linear Methods for Regression
Model Assessment and Selection
Deep Learning I
Deep Learning II
Societal Implications and Ethics
This schedule is tentative and subject to change as certain material may take longer/shorter. From time to time (as required), some notes may be posted on the BCIT Learning Hub. You must also read the supplementary material posted online.
Any student who needs special assistance in the event of a medical emergency or building evacuation (either because of a disability or for any other reason) should promptly inform their course instructor(s) and Accessibility Services of their personal circumstances.
Human Rights, Harassment and Discrimination:
The BCIT community is made up of individuals from every ability, background, experience and identity, each contributing uniquely to the richness and diversity of the BCIT community as a whole. In recognition of this, and the intrinsic value of our diversity, BCIT seeks to foster a climate of collaboration, understanding and mutual respect between all members of the community and ensure an inclusive accessible working and learning environment where everyone can succeed.
Respect, Diversity, and Inclusion is a supportive resource for both students and employees of BCIT, to foster a respectful learning and working environment. Any student who feels that they are experiencing discrimination or harassment (personal or human rights-related) can confidentially access this resource for advice and support. Please see Policy 7507 – Harassment and Discrimination and accompanying procedure.
Students should make themselves aware of additional Education, Administration, Safety and other BCIT policies listed at https://www.bcit.ca/about/administration/policies.shtml
Guidelines for School of Computing and Academic Studies
Students must successfully complete a course within a maximum of three (3) attempts at the course. Students with two attempts in a single course will be allowed to repeat the course only upon special written permission from the Associate Dean. Students who have not successfully completed a course within three attempts will not be eligible to graduate from their respective program.
I verify that the content of this course outline is current.
Chi En Huang, Program Head
August 23, 2021
I verify that this course outline has been reviewed.
Mirela Gutica, Program Head
August 24, 2021
I verify that this course outline has been reviewed and complies with BCIT policy.
Aaron Hunter, Acting Associate Dean
August 24, 2021
Note: Should changes be required to the content of this course outline, students will be given reasonable notice.