Sessional Lecturer - MIE- Introduction to Data Science and Analytics

Description

Course number and title: MIE
1624S – Introduction to Data Science and Analytics

Course 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.

The course 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.

Campus:
St. George (Downtown Toronto)

Sessional dates of appointment:
January to April 2027

$30,000 (per half course inclusive of vacation pay)

• Preparation of lectures and course materials
• Delivery of lectures
• Supervision of Teaching Assistants
• Setting and marking of tests and exams
• Evaluation of final grades
• Contact with students

• Strong record of presenting lectures or acting as a teaching assistant
• Considerable depth of knowledge and experience in the subject area
• Excellent communication skills – both oral and written
• Professional Engineer (P.Eng.) or Limited License (LEL) strongly preferred
• Engineering Intern (EIT) acceptable

The University of Toronto embraces diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA) and strives to make recruitment, assessment and selection processes as accessible as possible. Applicants with disabilities may request accommodations at any point during the application and hiring process by contacting