Sessional Lecturer, INF2179H - Machine Learning with Applications in Python (42872)
Sessional Lecturer, INF2179H - Machine Learning with Applications in Python (42872)
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Job Description
University of Toronto
Faculty of Information
Sessional Lecturer
Winter Term 2026 (January - April)
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 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:January 1 2026 - April 30 2026
Salary:
Sessional Lecturer I: $10300
Sessional Lecturer I Long Term: $10764
Sessional Lecturer II $11021
Sessional Lecturer II Long Term: $11227
Sessional Lecturer III: $11279
Sessional Lecturer III Long Term: $11485
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 Masters 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:June 3 2025
Application Process:Applicants must submit a CV and a completed CUPE 3902 Unit 3 application form in one pdf file to the attention of:
Melissa Szopa Administrative Coordinator Academic
Faculty of Information 140 St. George Street
University of Toronto
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.
Employment Type
Contract
