T-CAIREM Computing in Medicine courses

Overview

From Electronic Health Records and medical imaging to wearable devices and remote monitoring, technology enables healthcare providers to collect and examine vast amounts of data to gain insights. However, as data becomes increasingly pervasive in medicine, it has become more critical for health professionals and clinicians to have the skills to automate analyses using Artificial Intelligence (AI).

T-CAIREM is pleased to offer three standalone 5-week professional development courses to participants who would like to learn more about the fascinating field of AI in medicine. These self-directed online courses will provide learners with a comprehensive introduction to using data science in the Python programming language for medical applications.

Course Delivery

To accommodate learners of different levels, there are three separate courses available. Each course has assignments and takes place over a five-week window. Participants can complete each course on their own time at their own pace.

All three courses will be taught via video lessons using the University of Toronto's QUERCUS system. Students will be able to interact and ask questions directly to the instructor.

A Certificate of Completion and pass/fail grades will be issued for each course to participants who complete the required assignments in the allotted five-week period.

You don't need to take all three courses if you don't want to. Each course is treated as a separate standalone component for learners at different phases of their educational journey.

Course Descriptions

Participants will learn how to use powerful tools to analyze time-series data, process images, train machine-learning models, and create visualizations. By the end of the three-part series of courses, participants will come away with the skills and mindset needed to delve into tasks ranging from speech analysis to image classification.

COURSE 1: Basic Programming
Learn to write basic algorithms using the Python programming language in this 5-week course.
Dates: January 25, 2025 to February 11, 2025.
What you'll learn in the Basic Programming course

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COURSE 2: Data Science
Work with different types of data.
Dates: February 25, 2025 to March 25, 2025.
What you'll learn in the Data Science course

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COURSE 3: Machine Learning
Learn the terminology, execute machine learning pipelines, and program ML to make decisions.
Dates: April 8, 2025 to May 6, 2025.
What you'll learn in the Machine Learning course

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Syllabus THIS NEEDS TO BE UPDATED WITH INFO FROM RUTVIK'S EDITS TO ALEX'S GITHUB PAGE: https://tcairem-medicine-computing.netlify.app/

The syllabus is composed of 10 live lectures that will be delivered weekly from Wednesday, June 5, 2024, to August 7, 2024, from 7pm to 9:30pm.

Participants are expected to have some familiarity with programming, ideally in Python. To see the prerequisite knowledge required for this course or get a refresher in Python, participants are strongly encouraged to look through the materials in the Syllabus/Review before the first online session.

We will be using Google Colab for most of the lecture materials, in-class exercises, and assignments which the instructor will explain in the first session. All that is required to participate in the course is internet access and a free Google account. We will pre-enroll all students in the University of Toronto's QUERCUS online learning system.

Expectations

Each course requires timely completion of all assignments to receive a Certificate of Completion.

Course participants are expected to have some familiarity with programming, ideally in the Python programming language. To see the prerequisite knowledge required for this course or get a refresher in Python, students are strongly encouraged to review the syllabus.

Tuition

Each self-directed course is $1500 CAD and includes all materials.

Each in-person course is $2,000 and includes all materials.

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Meet the Instructor

Alex Mariakakis is an Assistant Professor in the Department of Computer Science at the University of Toronto and an Affiliate Scientist at Techna. He runs the Computational Health and Interaction (CHAI) lab, which leverages ubiquitous and emergent technologies to address problems related to people’s health and well-being.

What is Quercus?

Quercus is a learning management engine, and is the University of Toronto’s primary online teaching and learning platform.

Quercus is a web-based platform for accessing course content, submitting assessments, and interacting with your instructor and other learners. Your Quercus course site will be the “virtual classroom” where you, your instructor, and other course participants will interact throughout the course. You will receive a detailed schedule for your course and information about how Quercus will be used for all course formats (in-class, online and hybrid) in your Course Outline at the beginning of your course.

Contact

You can send any questions to t.cairem@utoronto.ca.