Sessional Lecturer - MIE1624F - Introduction to Data Science and Analytics

University of Toronto • Toronto, ON

2d • Onsite

About The Position

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.

Requirements

• 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

Nice To Haves

• Professional Engineer (P.Eng.) or Limited License (LEL) is strongly preferred
• Engineering Intern (EIT) is also acceptable

Responsibilities

• 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

What This Job Offers

• Job Type: Part-time
• Education Level: No Education Listed