What we do.

Machine learning summer training program for women+ across Canada.

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Study machine learning.

Dive into the fundamentals of machine learning to see problems in different ways, answer important questions, and inspire confidence in your new skills.

A group of students from the 2022 cohort

Build enduring relationships.

Explore the world of AI with our speakers and lecturers, and refine your interests with guidance from your mentors and teaching assistants.

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Develop projects with a purpose.

Reinforce your new skills with team-driven machine learning projects. Raise each other up and collaborate on solutions that drive social progress.

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Share your voice.

AI thrives from a diversity of perspectives. Bring yours to our supportive network of women+ who are changing the culture in technology and shaping the future of AI as a tool for social good.

What you can expect.

Weeks 1 — 4 ML Bootcamp.

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20+ hours

of lectures from machine learning experts including Lab co-founder Dr. Doina Precup.

13+ hours

of special topic workshops from industry, academic, and social good guest speakers.

30+ hours

of dedicated TA support, hands-on exercises, and skill-based tutorials.

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20+ hours

of lectures from machine learning experts including Lab co-founder Dr. Doina Precup.

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13+ hours

of special topic workshops from industry, academic, and social good guest speakers.

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30+ hours

of dedicated TA support, hands-on exercises, and skill-based tutorials.

Weeks 5 — 7 Team projects.

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25+ hours

of supporting mentorship and expert project guidance.

100+ hours

of teamwork to develop ML projects for social good.

Weekly

social and networking opportunities to help you figure out where you want to go next.

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25+ hours

of supporting mentorship and expert project guidance.

Label

100+ hours

of teamwork to develop ML projects for social good.

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Weekly

social and networking opportunities to help you figure out where you want to go next.

A group of students from the 2022 cohort

Application timeline.

Jan 10 - Jan 31

Call for Applications

You submit your application online.

Jan 10 - Jan 31

Feb 1 - Mar 1

Selection

We review the applications and admit selected candidates to the program, or offer a position on the waitlist.

Feb 1 - Mar 1

March

Acceptance

We congratulate accepted applicants!

March

April

Preparation

The cohort is finalized and receives onboarding information to prepare for the program.

April

May 1

Program Launch

Meet the AI4Good Lab community!

May 1

Enhance your career.

We are committed to supporting your growth beyond the 7-week program.

Opportunity.

Gain exclusive access to job openings, internships, and other opportunities from our partners and AI network.

Growth.

Receive year-round invitations to Lab and partner events, including workshops hosted exclusively for AI4Good Lab alumni. Continue learning with Lab resources for alumni.

Involvement.

Stay involved with the Lab by returning as a TA or mentor. Attend program events including the Alumni Soirée and Industry Night.

Community.

Cultivate the relationships you’ve formed with your mentors, TAs, and peers. Keep in touch and experience the value of a supportive network.

Learn from experts in the field.

Rasha Kashef

Rasha Kashef

Assistant professor, Mila, University of Montréal

AI4Good Lab

Sanaz Mohammadjafari

PhD Candidate, Toronto Metropolitan University

Patrick Pilarski

Patrick Pilarski

Associate Professor, Canada CIFAR Artificial Intelligence Chair

Doina Precup

Dr. Doina Precup

Lab Founder, DeepMind, McGill University, Mila

Guillaume Rabusseau

Guillaume Rabusseau

Canada CIFAR AI Chair
Assistant Professor
Université de Montréal
Mila

Samrudhdhi Rangrej

Samrudhdhi Rangrej

PhD Candidate
McGill University

Siva Reddy

Siva Reddy

Facebook CIFAR AI Chair
Assistant Professor
McGill University
Mila

Matthew Schlegel

Matthew Schlegel

PhD Candidate
Amii, RLAAI
University of Alberta

Martha White

Martha White

Associate Professor
University of Alberta
RLAI and PI at AMII

FAQ.

Lab overview

The AI4Good Lab is an introductory program to machine learning for women+ 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). See 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. Participants will work in small groups with their assigned Teaching Assistant (TA) to practice what they’ve learned through exercises. The TAs are typically PhD students in Computer Science with specializations in Machine Learning or AI.
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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. Teams are supported by their TAs and up to 3 mentors who work in AI.

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 Toronto Metropolitan University.

We accept 30 participants per regional program for a total of 90 participants per year. 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.

The AI4Good Lab Program is entirely conducted in English. The application form is available in English and French.

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

The 2023 Lab will follow a hybrid model. Some components will be hosted online, and in-person components will be hosted in the three regional locations: Montreal, Toronto, Edmonton. Although it is strongly encouraged to take advantage of in-person networking opportunities, participants will not be obligated to attend in-person events. Alternate online options will be made available. Each location will determine which components of the program will be hosted in person.

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.

The 2023 program is running in Montreal, Edmonton, and Toronto from May 1st to June 20th. It is a full-time commitment that runs roughly during work hours (11AM - 6:30PM ET), with scheduled breaks throughout the day. The hours vary across Canadian time zones so virtual activities can be run synchronously. Each day features four 90 minute sessions with 15 minute breaks in between and a one hour lunch. Due to the intensive nature of the projects, many participants choose to work on their projects outside of Lab hours, including evenings and/or weekends. The program is designed to be fully immersive, so attendance at all lectures, talks, and workshops is required for all participants.

In-person attendance is strongly encouraged but not mandatory. The virtual program is accessible to anyone who is available during the program hours (11AM - 6:30PM EDT) and has a valid status to study or work in Canada. The Lab is exploring options for providing travel reimbursements to eligible participants for certain events, however the Lab will not be able to fully fund participants to move to a new city for the duration of the program. The stipend provided to all participants at the end of the program may be used to cover living expenses and travel costs as well.

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 2023, the regional programs will overlap virtually for the foundational components of the program which includes lectures, speakers, and some networking events.

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 regionally hosted events. 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 and social activities. Each location will determine which components of the program will be hosted in person and participants will be notified of these decisions to allow for advanced planning.

The AI4Good Lab is a full-time commitment (11 AM to 6:30 PM ET) that includes daily attendance at mandatory events and intensive studying and/or group work. The hours vary across Canadian time zones so virtual activities can be run at the same time. Each day features four 90 minute sessions with 15 minute breaks in between, including a one hour lunch. 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.

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 for internet and other tech accessories to ensure all participants can access the program without barriers.

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 with TAs in work groups to enhance participant understanding of the material. Attendance at lectures, talks, and workshops, however, is required for completion of the program.

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.

Eligibility

The ideal AI4Good Lab applicant is a woman+ who has a strong math background 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 an introductory program to machine learning and therefore not open to high school students, PhD 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.).

Our program is open to women+, which includes cisgender women, transgender women, non-binary people, and anyone who identifies as having experienced misogyny. The “+” in “woman+” is in no way intended to erase or minimize those for whom the term ‘woman’ doesn't apply or fully encapsulate their personal experiences. Rather the “+” is included to reach those who would benefit from our mission in creating opportunities for people whose genders have historically been underrepresented in the AI industry. We are committed to listening and growing as the conversation about the nuances and complexity of gender and its intersections evolves. Please read Our Story to learn more about why the program exists to support women+.

The purpose of the program is to introduce machine learning to those who otherwise may not have the opportunity to explore it in-depth. We welcome applicants with diverse educational backgrounds! 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 or the courage to pick up challenging concepts at a fast pace.

To keep up with the math concepts introduced in the lectures, participants should at least be familiar with linear algebra, probability, and/or calculus. The lecturers will offer a basic overview of what you’ll need to know as it applies to machine learning with the assumption that you have some background knowledge to build off of. 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. If you are accepted into the program and feel uncertain about your Python skills, we recommend reviewing the basics before the start of the program.

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.

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.

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

Applications

When you apply, you will not have the option to select a specific region. The selection committee will categorize applicants into the appropriate regional cohort (Montreal, Edmonton, Toronto) based on your location in Canada during the program. Although your preference may be taken into consideration, your cohort will be chosen to maximize the possibility of travel to in-person events while enabling you to collaborate virtually with peers in similar time-zones.

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):

  1. Provide a brief description of why you'd like to join the Lab.
     
  2. 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.
     
  3. The AI4Good Lab is devoted to the use of AI as a tool for social good. Please describe how this mission speaks to you.

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.

The call for applications opens in 2023 on January 10th, and closes on January 31st.

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 1st 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 1st 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 because we received an incorrect email address from an applicant.

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.

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 on one’s chances of receiving a spot if they are placed on the waitlist.

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

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.

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.

Other questions? Please email us at info@ai4goodlab.com

Join the Lab in your region.

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Montreal skyline

Montreal

Hosted by the AI4Good Lab headquarters team

Edmonton, Alberta

Edmonton

Hosted in partnership with the Alberta Machine Intelligence Institute

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Toronto

Hosted in partnership with Toronto Metropolitan University

What our alumni say.

Kamun Karl Itaj

“I think the Lab gave me the confidence that I could actually work in the AI industry, even though I did not study computer science. I am grateful that the AI4Good Lab helped me with creating a vision for my future.”

Kamun Karl Itaj
AI4Good Lab Alumni

Explore the projects from start to finish

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