Sessional Lecturer, INF2179H - Machine Learning with Applications in Python

University of Toronto
Faculty of Information

Sessional Lecturer

Summer Term 2026 – Session Y (May – August)

INF2179H  –  Machine Learning with Applications in Python   

Course Description: Machine learning has recently become the dominant field in AI research and constitutes the main part of the tools applied in industry-based AI positions. Business analysts, data scientists and AI engineers are required to know machine learning at different levels. The course will give a broad high-level overview of state-of-the-art machine learning methodologies. We shall focus on the application of these techniques to real-world data using the most advanced tools available for Python. The techniques will include: linear regression, basic techniques for classification, advanced regression and classification methods, and unsupervised learning. 

INF2179H  –  Machine Learning with Applications in Python   

Estimate of the course enrolment: 35

Estimate of TA Support:None anticipated. Estimate of 75 hours with enrollment of 36 or greater. Allocation of TA hours, if any, will be based on enrolment numbers. 

Class Schedule: TBD. You are required to be located in geographical proximity to the applicable University premises in order to attend and perform your duties on University premises as of the Starting Date.

Sessional dates of appointment: May 1, 2026 – August 31, 2026

Salary: 
Sessional Lecturer I: $10,696
Sessional Lecturer I Long Term: $11,445
Sessional Lecturer II $11,445
Sessional Lecturer II Long Term: $11,713
Sessional Lecturer III: $11,713
Sessional Lecturer III Long Term: $11,986

Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Qualifications: Preferably candidates will have a completed, or nearly completed, PhD degree in an area related to the course or a Master’s degree plus extensive professional experience in an area related to the course. Teaching experience is preferred.

Brief description of duties: Preparing course materials; delivering course content (e.g., seminars, lectures, and labs); developing and administering course assignments, tests & exams; grading; holding regular office hours. 

Application Deadline: Feb. 10, 2026

Application Process: Applicants must submit a CV and a completed CUPE 3902 Unit 3 application form  in one pdf file to the attention of:  

Nafiseh Yazdian, Administrative Coordinator
Faculty of Information, 140 St. George Street  University of Toronto
sessional.ischool@utoronto.ca

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II and Sessional Lecturer III in accordance with Article 14:12.