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First of all, I would like to thank ÐÇ¿Õ´«Ã½ÊÓƵ for giving me the opportunity to learn about different aspects of AI that are relevant to Mathematics. Throughout my journey as an AI Teaching Fellow, I have learned a lot from reading papers and watching educational videos. Also, thanks to my exchanges with the other AI Teaching Fellows (who are members of numerous departments other than mine), I came to understand different perspectives on AI. ÌýAlthough my mandate as a Fellow has now ended, education is a continuous learning process and I will continue to learn more about AI and will serve as an ambassador for AI from the perspective of Mathematics.

The materials found in this portfolio can be used in any Dawson Mathematics course, especially courses related to distances as well as those related to probability and statistics, such as the following:

201-016-REÌý Ìý Ìý Ìý Remedial Activities For Secondary IV Mathematics

201-015-REÌý Ìý Ìý Ìý Remedial Activities For Secondary V Mathematics

201-105-DWÌýÌýÌýÌýÌýÌý Linear Algebra

201-401-DWÌýÌýÌýÌýÌýÌý Statistics for Social Science

201-922-DWÌýÌýÌýÌýÌýÌý Introduction to Statistical Methods for Chemical Technology

201-BZS-05Ìý Ìý Ìý Ìý Probability and Statistics

201-NYC-05Ìý Ìý Ìý Ìý Linear Algebra

Also, I have started developing two courses:

75-hour option courseÌý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Introduction to Machine Learning

45-hour complementary courseÌý Ìý Ìý Ìý Ìý ÌýSolve AI Mystery Using Spreadsheets

Modules on AI Algorithms

1. Regression
2. Decision Tree

3. Naïve Bayes

4. K Nearest Neighbors

5. K-Means Clustering

Presentations

Presentation on Ped Day

Date: October 14, 2020

Title: Are AI-Powered Exam Proctoring Systems the Answer We Have Been Waiting For?

Abstract: To what extent can we detect and prevent cheating in exams through remote AI proctors? In this session, we will explore what is currently available, past experiences, and potentials for the future. We will highlight the practical and ethical concerns around monitoring students physically, as well as tracking their private data. We will also explore some alternatives to reduce cheating in exams.

Presenters: Jennifer Sigouin, Vanessa Gordon, Garry Chu, Carl Saucier-Bouffard, Ahmad Banki

(Slides Used during 2020 Ped Day)

Presentation on Pi Day

Date: March 12, 2021

Title:ÌýConcepts in AI Algorithms

Abstract: Do you know how machines sort emails? Can Toffoli score in his next NHL game? Is there any ethical issue in AI algorithms? We will explore these AI concepts together in this talk.

Presenter: Garry Chu

Textbooks

1. Hong Zhou (2020) Learn Data Mining Through Excel: A Step-by-Step Approach for Understanding Machine Learning Method.
2. Jiawei Han, Micheline Kamber and Jian Pei (2012) Data Mining: Concepts and Techniques, 3rd Edition.

Papers

1. Hanif Bhuiyan, Akm Ashiquzzaman, Tamanna Islam Juthi, Suzit Biswas & Jinat Ara (2018) A Survey of Existing E-Mail Spam Filtering Methods Considering Machine Learning Techniques. Available at:
   

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2. Emmanuel Gbenga Dada, Joseph Stephen Bassi, Haruna Chiroma, Shafi’i Muhammad Abdulhamid, Adebayo Olusola Adetunmbi & Opeyemi Emmanuel Ajibuwa (2019) Machine learning for email spam filtering: review, approaches and open research problems. Available at:
   

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3. Victoria Rodriquez, Karan Sharma & Dana Walker (2018) Data Breast Cancer Prediction with K-Nearest Neighbor Algorithm using Different Distance Measurements. Available at:
   

Videos & Documentaries

Lectures on Machine Learning Algorithms

• Andrew Ng (2016) Machine Learning. [Online video] Available at:
  
• StatQuest with Josh Starmer (2018) Machine Learning. [Online video] Available at:
  
• Edureka (2019) Machine Learning Full Course. [Online video] Available at:
  

AI Ethics

• A famous dilemma on Ethics of AI Algorithms (4 minutes)
  Patrick Lin (2015) The ethical dilemma of self-driving cars. [Online video] Available at:
  

• A short video clip on AI Ethics (8 minutes)
  Toby Walsh (2018) AI and Ethics. [Online video] Available at:
  

• A questionable way to predict voters’ behavior (57 minutes)
  TVO Original (March 3, 2021) Margin of Error. [Online video] Available at:
  

• Artificial Intelligence and Algorithms: pros and cons (42 minutes)
  Tilman Wolff and Ranga Yogeshwar (September 26, 2019) The Great Leap Forward. [Online video] Available at:
  

Bias in AI Algorithms

• Bias on Facial Recognition (8 minutes)
  Joy Buolamwini (March 29, 2017) How I’m fighting bias in algorithms. [Online video] Available at:
  

• How ‘Alexa’ is threatening the society’s trust in scientific expertise (54 minutes)
  Frédéric Bouchard (January 25, 2021) Science and Society. [Online audio] Available at:
  

• 5 types of Algorithmic Bias (11 minutes)
  Jabril Ashe (December 13, 2019) Algorithmic Bias and Fairness. [Online video] Available at:
  

Future of Jobs

• Will AI change all jobs? (45 minutes)
  CBC Gem (2020) The AI Race. [Online video] Available at:
  

• Will AI replace all jobs? (15 minutes)
  CGP Grey (August 13, 2014) Human Need Not Apply. [Online video] Available at: