MIE1624H: Introduction to Data Science and Analytics
Toronto, ON, CA
University of Toronto
The University of Toronto is a globally top-ranked public research university in Toronto, Ontario, Canada.Date Posted: 10/18/2024
Req ID: 40260
Faculty/Division: Faculty of Applied Science & Engineering
Department: Dept of Mechanical & Industrial Eng
Campus: St. George (Downtown Toronto)
Description: The objective of the course is to learn analytical models and overview quantitative algorithms for solving engineering and business problems. Data science or analytics is the process of deriving insights from data in order to make optimal decisions. It allows hundreds of companies and governments to save lives, increase profits and minimize resource usage. Considerable attention in the course is devoted to applications of computational and modeling algorithms to finance, risk management, marketing, health care, smart city projects, crime prevention, predictive maintenance, web and social media analytics, personal analytics, etc. We will show how various data science and analytics techniques such as basic statistics, regressions, uncertainty modeling, simulation and optimization modeling, data mining and machine learning, text analytics, artificial intelligence and visualizations can be implemented and applied using Python. Python and IBM Watson Analytics are modeling and visualization software used in this course. Practical aspects of computational models and case studies in Interactive Python are emphasized.
Estimated course enrolment: TBD
Estimated TA support: TBD
Class schedule: TBD
Sessional dates of appointment: January 2025 – April 2025
Salary: $15,000 (per half course inclusive of vacation pay) per section. 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.
Minimum qualifications: Applicants should have a strong record of presenting lectures or acting as a teaching assistant. Applicants must be able to demonstrate considerable depth of knowledge and experience in the subject area. The applicant must have excellent communication skills in both oral and written.
Description of duties: Preparation of lectures and course materials; delivery of lectures; supervision of Teaching Assistants; setting and marking of projects, tests and exams; evaluation of final grades; contact with students.
Application instructions: Please submit a Course Instructor Application Form, Resume and Teaching Dossier to the MIE Graduate Administrator (acting) by email to Jonathan Alexander at jonathan.alexander@utoronto.ca no later than October 31, 2024 at 11:59pm (Eastern Time). The Course Instructor Application Form can be found on the MIE Careers page at: https://www.mie.utoronto.ca/faculty-staff/careers/
If during the application and/or selection process you require accommodation due to a disability, please contact Jonathan Alexander at jonathan.alexander@utoronto.ca.
The appointment will be made at the earliest possible time before the commencement of classes by the Associate Chair (Graduate) of the Department of Mechanical and Industrial Engineering. No other offers or notices of the outcome of applications are authorized by the Department. Final availability of the position is contingent upon final course determination, enrolment, budgetary considerations, and the final determination of assignments flowing from Article 14:03 of the Collective Agreement.
This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.
It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.
Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.
Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.
All qualified candidates are encourage to apply; however, Canadians and permanent residents will be given priority.
Closing Date: 11/08/2024, 11:59PM EDT
**
This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.
It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.
Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.
Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Data Mining Engineering Finance Industrial Machine Learning Predictive Maintenance Python Statistics Teaching
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