Description
:Basic theory of machine learning. Application to engineering problems. Supervised and unsupervised learning. Neural networks. Convolutional neural nets. Large language models. Tools for developing machine learning models and software applications that incorporate machine learning. Quality assurance and operations (MLOps) of machine learning systems. Feature engineering and prompt engineering. Case studies in various domains.Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time ProfessorDate Posted (YYYY/MM/DD):
2026/05/06Applications must be received BEFORE (YYYY/MM/DD):
2026/06/07Expected Enrolment:
N/AApproval date:
2026/05/06Number of credits:
3Work Hours:
39Hourly Rate:
Enseignement / Teaching: $239.47 (2024-2025)The academic year starts on September 1 and ends on August 31.
These rates do not included vacation pay nor statutory pay.
These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.
Course type:
BPosting type:
Régulier / RegularLanguage of instruction:
Anglais | EnglishCompetence in second language:
PassiveCourse Schedule:
Lundi | Monday 14:30-16:00 Jeudi | Thursday 16:00-17:30 -Requirements:
Excellent knowledge of course subject matter, demonstrated by having taught similar or related courses, or demonstrated by relevant work experience. Applicants must also be licensed as a Professional Engineer. Regular applicants must have a doctorate and it should be in a field related to the course (especially in the case where the course is more specialized), if not, they must have a relevant work experience in a field related to the course, after having obtained their Ph.D.
Please include your P.Eng. License number and province of registration when applying.
Additional Information and/or Comments:
An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience.
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