Experience the AI4Good Lab in Montreal.

For healthcare. For education. For good.
What will you build AI for?

Hosted by the AI4Good Lab Headquarters team.

Stationed in Montreal, Headquarters runs the Montreal regional program and organizes expansion across Canada.

History of the Montreal Program.

Professor Doina Precup and Angelique Mannella founded the Lab in Montreal as a direct response to the lack of diversity in the AI industry. Since 2017, the Montreal Program has trained over 130 women with the skills to start their careers, succeed in leadership roles, and work towards a more inclusive tech culture. The Montreal program welcomes 30 participants each year.

Discover the AI Ecosystem in Quebec.

With significant government and private investment, Quebec is a competitive centre for innovation and technology in Canada. Explore the unique cultural offerings of Montreal and get to know the local tech community.

Different regions, one Lab.

Like different classes for the same course, the regional programs all offer the same core education while showcasing the vibrant local identity of each AI community. Whether you join us from Montreal, Edmonton, or Toronto, the skills and network you gain at the Lab will kickstart your journey into AI.

Our program.

Our 7-week program (May 2nd – June 21st) is designed to prepare you with the necessary skills to build your own machine learning projects, from start to finish, while offering an unmatched opportunity for mentorship and career exploration.

Weeks 1 — 4 ML Bootcamp.

Program Launch.

The first day of the program kicks off with words of advice and encouragement from our co-founders and partners. Get the chance to meet your peers and TAs and become familiar with the flow of the next 7 weeks.

Lectures.

Get experience with processing data, training models, and using ML tools. Progress from the fundamentals of machine learning through neural networks (NNs, CNNs, RNNs) and on to reinforcement learning.

Big Picture.

Learn how AI is changing industries, explore the cutting edge of AI research, and discuss issues on social good and AI ethics with our guest speakers.

Network.

Get excited for Industry Night where you will meet representatives from our partner organizations, expand your network, and explore the opportunities available to you in the industry.

Practice.

Solve hands-on exercises, put your new skills into action at our mini data-processing hackathon, and have all your questions answered by your graduate-level TAs.

Weeks 5 — 7 Team Projects.

Experience.

Cement your newly acquired knowledge in AI by developing a machine learning prototype, from start to finish.

Teamwork.

Discover the best way to collaborate on technical projects by working in teams to build your prototype.

Mentorship.

Enhance your projects with mentorship from AI experts in research and industry.

For Good.

Use your project as an opportunity to explore solutions to real-world problems and evolve your understanding of ethical design principles.

Demo Day.

The final day of the program is a celebration of the hard work put in by all the project teams in your cohort. Pitch your project to a panel of AI experts and mingle with all those who’ve supported you along the way. Select teams may be chosen to extend their projects with additional support from the AI4Good Lab and our collaborators.

Learn from experts in the field.

Rasha Kashef

Assistant professor, Mila, University of Montréal

Sanaz Mohammadjafari

PhD Candidate, Toronto Metropolitan University

Patrick Pilarski

Associate Professor, Canada CIFAR Artificial Intelligence Chair

Dr. Doina Precup

Lab Founder, DeepMind, McGill University, Mila

Guillaume Rabusseau

Canada CIFAR AI Chair
Assistant Professor
Université de Montréal
Mila

Samrudhdhi Rangrej

PhD Candidate
McGill University

Siva Reddy

Facebook CIFAR AI Chair
Assistant Professor
McGill University
Mila

Matthew Schlegel

PhD Candidate
Amii, RLAAI
University of Alberta

Martha White

Associate Professor
University of Alberta
RLAI and PI at AMII

“Start before you're ready. You don't need to have done something before nor mastered everything that you think you need to master in order to start making a difference and making an impact.”

Angelique Mannella
AI4Good Lab Co-Founder, Amazon, AM Consulting

Meet and work with AI leaders.

Alaa Abdelgawad

Zafarali Ahmed

Manager, PwC

Dr. Sedef Akinli Kocak

Applied AI Project Manager
Vector Institute

Adrien Ali Taïga

Research associate, Google

Ehsan Amjadian

Director of AI, RBC

Muhammad Anwar Ul Haq

PhD candidate, University of Toronto, Vector

Arjun Asokakumar

Director, Data Science, RBC

Nadia Blostein

MS, Integrated Program in Neurosceience @ McGill University

Chantelle Bourgeois

MNP

Alissa Brayley

Data Scientist, RBC

Neil Burch

MSc Student, McGill University

Ann Crabtree

Clinical Associate Professor, University of Calgary

Sara El-Shawa

Applied Machine Learning Intern
Vector Institute

Joud El-Shawa

Andy Forest

Executive Director, STEAMlabs

Alexandre Frechette

Research Engineer, DeepMind

Alona Fyshe

Assistant Professor, Amii

Alyssa Gagne

Senior Associate, PwC

Anita Gergely

Research Developer
DeepMind

Maria Gini

CSE Distinguished Professor, Department of Computer
Science and Engineering, University of Minnesota

Ross Goroshin

Senior Data Scientist, Manulife

Courtney Handford

Physician – Psychiatry Resident, Dalhousie University

Nidhi Hegde

Associate Professor
University of Alberta

Natasha Jaques

Research Scientist
Google
UC Berkeley

Faezeh Khabbaz

Manager Data Science, PricewaterhouseCoopers LLP (PwC)

Brenden Kumarasamy

Parisa Lak

Research scientist, DeepMind

Kate Larson

Professor
University of Waterloo
DeepMind

Elaine Lau

AI4Good Lab Alumni
Data Scientist Intern at TD Bank

Chun Lei He

Lead Data Scientist, Manulife

Ayesha Liaqat

Maureen Mai

PhD Candidate, University of Waterloo

Mina Mirshahi

Data Developer, MNP Digital

Joseph Modayil

Sr. Data Scientist, Manulife

Debarati Nath

Elmira Navidbakhsh

Deval Pandya

Director of AI Engineering
Vector Institute

Mojgan Saeidi

Senior data scientist, Manulife

Dr. Bahar Sateli

Manager in AI & Advanced Analytics
PWC

Sylvia Shiah

Lead Professional Development, Vector Institue

Brenda Shivanandan

Executive Director, STEAMlabs

Jia Song

Senior Director of Analytics, Global Cyber Security, RBC

David Szepesvari

Research Developer, DeepMind

Cristina Vasconcelos

Research Software Engineer
Google

Jodie Wallis

Global Chief, Analytics Officer
Manulife

Connor Wright

Partnerships Manager
Montreal AI Ethics Institute

Jie Wu

Software Engineer, Google

Kelly Zheng

Montreal collaborators.

Participants.

Lily Andruschak

Vivienne Crowe

Yangjingming Fu

Run Guo

Cindy Hallak

Yuan Hong

Shih-Ching Hsu

Nghi Huynh

Sophia Jit

Aakanksha Khandwaha

Kate Kim

Mariam Konate

Marie-Elise Latorre

Mingfei Li

Yiran Li

Ridhi Mittal

Achouch Mounia

Eptehal Nashnoush

Laura Paul

Xinyu Qian

Keelin Sekerka-Bajbus

Yuan Wang

Alex Whidden

Kiara Wimbush

Jocelyn Wong

Yimei Yang

Shirley Zhang

Xinyi Zhang

Should I apply?

You want to gain technical skills and hands-on experience in AI.

You want to build relationships with AI professionals.

You care about enhancing society with technology.

You value teamwork and diverse perspectives.

Am I eligible?

You are a woman or gender minority.

You have a valid status in Canada (citizen, resident, study or work permit).

You are registered at a Canadian post-secondary institution or have recently graduated.

Do I qualify?

You have some experience programming in Python.

You have a strong background in at least one math subject: linear algebra (preferred), multivariable calculus, statistics, probability.

No prior experience in machine learning necessary!

FAQ.

Lab overview

What is the AI4Good Lab?

The AI4Good Lab is an introductory program to machine learning for women and gender minorities with some programming background and intermediate to no experience in machine learning. The Lab runs for 7 weeks during the summer and is split into 2 sections (the Bootcamp and Project weeks). Click here for a detailed description of the program.

ML Bootcamp: The curriculum section is an intensive introductory bootcamp to machine learning and AI, which takes place over the first 4 weeks of the program. During this time, participants attend lectures, talks, workshops, and networking events.

Team projects: The Project section takes place over the last 3 weeks, during which participants use the knowledge gained during the bootcamp and work in teams to develop an AI/ML prototype that addresses a social good issue.

Who runs the AI4Good Lab?

The AI4Good Lab is a non-profit program supported by a variety of partners and run by our management team. Our founding partners are the OSMO foundation and CIFAR, and we are supported by corporate, academic, and government organizations. The AI4Good Lab headquarters is stationed in Montreal, where we run the local Montreal program and organize expansion across Canada. The Edmonton program is run in collaboration with the Alberta Machine Intelligence Institute (Amii) and the Toronto program is run in collaboration with CIFAR.

How many participants are accepted into each program?

We accept 30 participants per regional program. The small cohort size is chosen to ensure we can prioritize the growth and understanding of our participants, while creating an environment that enables them to form meaningful relationships with their peers and educators.

What are the language requirements of the program?

The AI4Good Lab Program is entirely conducted in English. The application form is also in English.

There are many alternatives for learning AI. Why should I join the AI4Good Lab?

Opportunities for individual learning are abundant, but the Lab addresses one of the biggest barriers for underrepresented individuals in the industry: access to mentorship and deep professional networks. We connect participants with mentors and educators who are experienced AI practitioners in the industry. These experts have joined us to guide our participants in their learning, and are eager to welcome them into the AI community.

Our goal is to open doors for those whose genders are underrepresented in the AI industry. We aim to achieve this in the following ways:

We accept participants from a broad range of educational backgrounds and experiences.
Our program is tuition-free and we provide stipends and reimbursements to ensure equal access to the program.
Our education model centres curiosity-driven exploration and collaborative learning instead of competition and grades.

From mentorship and financial support to our educational ethos, this program is unmatched in its ambition to drive the culture of technology towards inclusion and representation.

Program details

Will the Lab be in-person or virtual in 2022?

We can guarantee that the Lab will run virtually in 2022, however in-person programming opportunities will be decided on a region-specific basis by March 2022 in consideration of the rapidly changing circumstances of COVID-19. All selected participants will be given further details to allow for advanced planning. Regardless of the format, the Lab will continue to ensure the program’s accessibility for all participants.

When is the program and what is the time commitment?

The 2022 program is running in Montreal, Edmonton, and Toronto from May 2nd to June 21st. It is a full-time commitment that runs during work hours and some evenings/weekends, with scheduled breaks throughout the day. The program is designed to be fully immersive, so attendance at all lectures, talks, and workshops is required for all participants.

Can I attend the program if I don’t live in one of the cities where the program is hosted?

The virtual program is accessible to anyone who is available during the program hours and has a valid status to study or work in Canada. In-person components of the program will be determined as COVID-19 restrictions for the summer of 2022 are clarified on a regional basis. If in-person attendance is required, travel bursaries may be available to eligible participants.

What’s the difference between the Montreal, Edmonton, and Toronto programs?

Like different classes for the same course, each regional program of the AI4Good Lab offers participants the same value of education and opportunities for career advancement.

In 2022, the regional programs will overlap virtually for the foundational components of the program which includes lectures, speakers, Industry Night, and the Alumni Soirée.

The distinct identities of each program arise from the different people involved; each program is run by a different team, has its own distinct cohort of participants and TAs, and has some differences in the partners and mentors available to participants. The Montreal program is run by the AI4Good Lab headquarters, the Edmonton program is run in collaboration with Amii, and the Toronto program is run in collaboration with Toronto Metropolitan University.

Each regional program will run its own study and project groups, as well as some events such as Demo Day and social activities. These region-specific activities may be either virtual or in-person depending on the specific requirements of each region.

Can I work or take other classes during the program?

The AI4Good Lab is a full-time commitment (6 to 8+ hours) that includes daily attendance at mandatory events and intensive studying and/or group work. In our experience, it is impossible to balance external responsibilities with full participation in the AI4Good Lab. If you are accepted and currently employed, we recommend receiving a leave of absence from your employer before accepting your spot.

What are the technological requirements of the program?

Participants will be expected to have access to a laptop / computer, high-speed internet (at least 70mbps download speeds), and earphones/headphones with a microphone. We may offer reimbursements to ensure all participants can access the program without barriers.

How is the program graded?

At the AI4Good Lab, we prioritize a peer-driven, curiosity-based learning environment. No grades are given. Exercises will not be graded, but may be reviewed in work groups to enhance participant understanding of the material. Attendance at all lectures, talks, and workshops, however, is required for completion of the program.

Does the Lab offer certificates?

All AI4Good Lab participants who successfully complete the program will receive a certificate of completion. The AI4Good Lab is not an accredited institution and does not give official degrees.

Will the AI4Good Lab provide references for employment opportunities?

After completion of the program, the AI4Good Lab management team can provide confirmation that a participant has attended and completed the program, however the management team cannot act as a performance or supervisory reference. It is the responsibility of the participant to develop relationships with the professors, TAs, and/or mentors during the program who may agree to attest to the performance of the participant.

Eligibility

Who can apply to the Lab?

The ideal AI4Good Lab applicant is a woman or gender minority who has a strong math background (preferably linear algebra) as well as some knowledge of Python (through coursework, personal projects, work experience, etc.).

All participants must be current students at a post-secondary institution (University, college, etc.), or recent graduates. The program is not designed for high school students or those who are already experienced in ML.

To be accepted, applicants must have a valid status in Canada (citizen, resident, study or work permit, etc.).

My background doesn’t quite align with the math/coding requirements. Can I still apply?

The purpose of the program is to introduce machine learning to those who otherwise may not have the opportunity to explore it in-depth. Participants do not need to have a mathematics or computer science degree to succeed in the program, however it is an intensive and fast-paced program that requires previous knowledge of coding and math.

The Mathematics for Machine Learning module in the program reviews the basics of linear algebra, probability, and calculus in the first two days of the program. This is meant to serve as a review that covers content typically taught in separate courses over several months, so it is essential that participants have previous knowledge of these subjects. You may review the following topics for further insight: probability distribution, Bayesian estimation, basics of linear algebra, calculus derivatives, and regression.

The program does not teach its participants to program, and all coursework is performed in Python. Participants are expected to have prior experience coding in Python from activities such as coursework, personal projects, work experience, etc.

Applicants do not need to know any machine learning prior to the program.

Unfortunately we are not available to review your background or application. If you are uncertain, we encourage you to apply.

Why do I need a valid status in Canada?

To reduce economic barriers, all participants are provided with a stipend. It is the responsibility of the participant to ensure that their status in Canada enables them to receive this payment, which may be issued in the form of a Canadian cheque, and be able to report this income on their applicable taxes.

Can I forfeit my stipend so I can attend because I don’t have valid status in Canada?

Economic support during the program is a key pillar that equalizes all participants. It is a required part of the program.

Applications

Can I apply to a specific region?

To ensure that every applicant has the highest likelihood of acceptance, applications are not submitted to a specific program. Applicants will be considered equally for all program locations, and will be offered a spot in a specific program location if they are accepted. The waiting list is also specific to location. Applicants will be most strongly considered for the location closest to their current or most recent attended University. Their location of residence and educational background may also be considered.

What will I need to submit as part of the application?

Applicants will need to log into their Google accounts to submit to our Google Form application.

To apply, applicants will need to submit their CV/Resume and a copy of their most recent transcript (unofficial transcripts are accepted). The application also consists of 3 short-essay questions (500 words max):

Provide a brief description of why you'd like to join the Lab.
The AI4Good Lab is a collaborative learning environment, where all participants will work in groups throughout the curriculum and project phases. Please describe your experiences with collaborative learning and describe how you believe you will contribute to a supportive peer-learning environment.
The AI4Good Lab is devoted to the use of AI as a tool for social good. Please describe how this mission speaks to you.

What can I do to strengthen my application?

We encourage applicants to provide concrete examples for every essay question, drawing from personal history, projects, or activities that they were directly involved in to support their responses. We are unable to give feedback on individual applications.

What is the timeline for acceptance into the program?

The call for applications opens in 2022 on January 15th, and closes on February 15th.

After the call closes, the selection committee will process the applications in 3-4 weeks. The selection committee consists of our founders, management team, and committee members from our partners.

All applicants will be notified of their selection status by March 15th at the latest. Those on the waitlist will be notified of selection on a rolling basis. Applicants who do not hear from us by March 15th may contact us at info@ai4goodlab.com to inquire as to the status of their application. The most common reason for a lack of response is due to an incorrect email address.

Each year we evaluate a competitive pool of applicants for limited spots, so we encourage rejected candidates to re-apply the following year. We are unable to give feedback or suggestions to those who are not accepted.

Where am I on the waitlist?

In every cohort, we strive for diversity in terms of educational background, location, University, etc. For these reasons, the waitlist does not have a specific order. Participants are selected off the waitlist due to a variety of factors, and we cannot give further information one’s chances of receiving a spot if they are placed on the waitlist.

If I receive an acceptance, how long will I have to confirm my spot?

Accepted applicants will have 4 business days to confirm their spot before the opportunity is passed to someone on the waitlist. Given the full-time requirements of the program, many participants will need to make arrangements well in advance to attend. This means applicants who receive acceptances need to notify us ASAP if they are unable to attend the program in order to allow others the opportunity to plan ahead.

Costs

How much does it cost to attend the Lab?

The only cost to attend the Lab is a $75 registration fee for accepted applicants to confirm their spot in the program.

There is no cost to apply and there are no tuition fees.

Do students receive a stipend?

Every participant receives a stipend after completion of the program. The minimum stipend amount is $500, and the final amount is determined on a yearly basis by the end of the program. The final amount is determined by budgeting activities and is not dependent on the performance of the participants.

Past projects.

Cash the Trash

dose.io

Epi Health

Focus

Happy path

HealthWhere

Implexis AI

Mood Ring

N(A)RRAT(I)VE

PhysiFeedback

RecordLing

Reimagine

Scam Hound

SoQuo

ZeroCa.ml

“The Lab is one of the best opportunities I've had in my life. I learned so much not only about AI, machine learning and the industry but also about myself. The connections made and the bonds formed with the other participants will be preciously kept for a long time.”

Aurélie Nguyen
AI4Good Lab Alumni

Meet the 2022 cohort

Learn more

Quebec is taking action to promote diversity in AI.

AI4Good Lab in collaboration with Québec

The Quebec Ministry of Economy and Innovation is enabling the AI4Good Lab to continue its mission in providing access to training and mentorship for underrepresented individuals in AI through the NovaScience Program support for “Training initiatives in artificial intelligence (AI)” in 2021 and 2022.

National Partners.

Founding Partners

Expansion Partners

Title sponsors

Key sponsors

Community sponsors

Experi­ence the AI4Good Lab in Montre­al.