AI MASTER’S: BUILDING ONTARIO’S AI ECOSYSTEM

Français

The Vector Institute is building an AI workforce to drive the competitiveness of Ontario-based companies and labs and to strengthen Ontario’s position as a global destination in AI. The Vector Scholarship in Artificial Intelligence, valued at $17,500, helps to attract the best and brightest students to study in AI-related master’s programs in Ontario. There are currently over 20 master’s programs in Ontario recognized by the Vector Institute for equipping graduates with AI skills and competencies sought by industry. These include new and expanded programs in core technical and complementary areas such as business and health. By providing an increasing number of students and graduates with meaningful professional development and linking them to compelling internship and career opportunities through the Vector Digital Talent Hub, the Vector Institute is positioning Ontario to lead the way in AI adoption.

VECTOR SCHOLARSHIP IN ARTIFICIAL INTELLIGENCE

Vector Scholarship in Artificial Intelligence 2021-22: Nomination period will open on January 4, 2021 and will close March 24, 2021.

All nomination forms and templates will be announced at this time. All forms that are required to submit nominations will be open at this time including referee forms and a suggested template for submitting nominee statements.

Inquiries about the scholarship can be sent to aimasters@vectorinstitute.ai.

The Vector Scholarship in Artificial Intelligence supports the recruitment of top students to AI-related master’s programs in Ontario. Valued at $17,500 for one year of full-time study at an Ontario university, these merit-based entrance awards recognize exceptional candidates pursuing a master’s program recognized by the Vector Institute or who are following an individualized study path that is demonstrably AI-focused. Students in both core technical programs and complementary fields such as business and health are eligible for nomination.

Scholarship recipients by Institution:

2020-21 Recipients
University
Program Name
Electrical and Computer Engineering Kyrollos, Daniel
MSc in Computer Science
Baxi, Manmeet
Kaspour, Shamisa
Liu, Weiting
Singhal, Aditya
Swerhun, Mekaal
Master of Computer Science Fathi, Kiavash
MASc in Applied Physics
Filipovich, Matthew
MASc in ECE
Beitollahi, Mahdi
Gasca Cervantes, Eduardo
Greisman, Austin
Gupta, Divij
Lau, Clinton
Obadinma, Stephen
Zhao, Jianxiang
MASc in Mathematics and Engineering
Gronowski, Adam
Master of Management Analytics
Natarajan, Janani
Master of Management in Artificial Intelligence
Arora, Gurkanwal
Lei, Gavin
Raza, Mohammad
Syed Rahmathulla, Wafiq
Wu, Ruihan
MSc in Computer Science
Ansari, Minhaj
Everitt, Brittaney
Scott, Katy
Stuart, Duncan
Su, Zitong
Theriault, Rachel
Collaborative Specialization in AI Master’s
El-Shawa, Sara
Salem, Mahmoud
Master’s of Information Technology Security Ahmed, Farhan
Master of Applied Science in Electrical and Computer Engineering
Zhang, Han
Master’s in Computer Science
Mvula, Paul
Nazari, Ehsan
Health Services Research
Nedadur, Rashmi
MASc in Aerospace Studies
Lu, Shichen
Nadeau, Philippe
Qian, Jingxing
Wu, Yuchen
Yuan, Zhaocong
MASc in ECE
de Souza Severo, Daniel
Jia, Hengrui
MASc in Mechanical & Industrial Engineering
Patel, Raj
Tian, Sophie (Sijie)
Wong, Rachel
Xu, Meng (Katie)
Master of Management Analytics
Donovan, John Connor (Connor)
El Mellouki, Zineb
Ji, Yuan
Moon, So Hyun (Stella)
So Hyun (Stella), Sidharth
Puccini, Aaryn
Wisco, Asia
Zegarmistrz, Marcin
Zizek, William (Bill)
MSc Health Informatics
Keenan, Charles
Lin, Charis
Wang, Yi Li
MSc in Applied Computing
An, Ruijian
Arivazhagan, Manoj Ghuhan
Bhattacharjee, Sourav
Brock, Stephen
Ellis, Jack
Feng, Yiwen
Guo, Yijie
Landsman, David
Liu, Shanning
Ngo, William
Roy, Subhayan
Zhao, Luxi
MSc in Computer Science
El Sanyoura, Lana
Hao, Siqi
Mansouri, Farnam
MASc in ECE
MohammadMahdi, Naseri
MASc in Systems Design Engineering
Hemmatirad, Kimia
Master of Data Science and Artificial Intelligence
Melgarejo Lermas, Irene
MMath in Computer Science
Alagappan, Solaiappan
Herman, Daniel
VanBerlo, Blake
Master of Science in Computer Science- Artificial Intelligence [with/without Co-Operative Education]
Gautam, Vishakha
Hora, Sheena
Jouyandeh, Farzaneh
Patel, Himanshu
Roy, Shuvendu
Master of Data Analytics
El Rachidi, Firas
Joseph, Pauline
MSc in Computer Science
Keyes, Andrew
Wang, Wei
Younesi, Mohammad
Zhang, Qinggang
Master of Business Analytics (MBAN) Cong, Chang
Master of Management in Artificial Intelligence (MMAI)
Haji Seyed Hassani, Amir
Luhm Silva, Ricardo
Sterling, Brigid
MSc in Computer Science
Meka, Bhargavi
Sy, Steniel
Ye, Isaac

 

2019-20 Recipients
University
Program Name
Computer Science Nokhbeh Zaeem, Mohammad
Economics Foroutan, Frohan
Computer Science (Collaborative Specialization in AI) Foxcroft, Jeremy
Engineering (Collaborative Specialization in AI)
Allam, Abdelrahman
Bauman, Valerie
Shekhar, Shashank
Computer Science
Emu, Mahzabeen
Heydrich, Tim
Kamal, Farjana
Zhang, Shengyi
Computational Science & Engineering White, Lindsay
Electrical & Computer Engineering
Dai, Linhui
Scott, Ryan
Computer Science
Fernandes, Johan
Larocque, William
Li, Wei
Templeton, Julian
Wang, Ning
Computer Science
Jiang, Bote
Kaczmarek, Emily
Electrical & Computer Engineering Babaei, Hossein
Management in Artificial Intelligence
Banh, Alexander
Jones, Kyle
Sehdev, Amrit
Singh, Gunpreet
Skingle, Brendan
Smith, Mark
Wang, Jiaxi (Nicky)
Data Science & Analytics
Anumanchineni, Harish
Malika, Garima
Patel, Kshirabadhi
Aerospace Science & Engineering
Bianchi, Mollie
Grover, Abhinav
Applied Computing
Habib, Faisal
Kumar, Shakti
Le, Huu Uyen Phuong
Nanderian, Pantea
Parker, Jerrod
Saha, Rohit
Wei, Lixiang
Biomedical Engineering
Sabo, Andrea
Grover, Abhinav
Computer Science
Bharadwaj, Homanga
Cao, Tianshi
Li, Andrew
Qiu, Han Jie
Wu, Qiongsi
Health Informatics
DeWit, Michael
Perron, Rachelle
Shen, An-Qi
Wang, Jianmin (Jamie)
Mechanical & Industrial Engineering
Pogacar, Frances
Yang, Hojin
Management Analytics
Bani, Denisa
He, Xichen
Priya, Varshini G
Resnick, Adam
Computer Science Duan, Haonan
Data Science
McCorriston, Melissa
Sundrelingam, Vaakesan
Electrical & Computer Engineering Guo, Xinyu
Systems Design
Adnan, Mohammed
Rasoolijaberi, Maral
Collaborative Specialization in AI
Tayeh, Tareq
Wang, Huanchi
Data Analytics
Bhasin, Deepanshu
Popli, Simran
Wen, Yizhe
Yerubandi, Dhanusha
Business Analytics
Kur, Daniel
Palangat, Revthi Jayarajan
Computer Science Kaur, Jasmeet
2018-19 Recipients
University
Program Name
Biomedical Engineering (Data Science Specialization) Fernandes, Alexander
Computer Science
Tassone, Joseph
Yan, Peizi
Computer Science (AI)
Gerolami, Justin
Lam, Jason Tzu-Kei
Electrical and Computer Engineering
Edraki, Amin
Elsherbiny, Habiba
Mahdy, Basma
Mohammadalizadehbakhtevari, Pedram
Yang, Xiaoyu
Management in Artificial Intelligence
Burns, Levi
Fotak, Meghan
Hennick, Tyler
Sopik, Victoria
Yee, Brian
Computer Science (Specialization in AI)
Kazmi, Arslan
Sun, Wanrong
Engineering (Specialization in AI)
Szentimrey, Hannah
Tahsien, Syeda Manjia
Computer Science Stahlke, Samantha
Computer Science (AI)
Lucaci, Diana
Meihong, Chen
Yuan, Gao
Aerospace Science and Engineering
Dong, Ke
Hall, Adam
Samavi, Sepehr
Wong, Jeremy
Applied Computing
Bhaskara, Subrahmanya Vineeth
Desai, Sneha
Gou, Stephen
Huang, Gary
Murali, Ranjani
Qie, Chenzi
Wang, Shirly
Computer Science
Gao, Jun
Grewal, Karan Raj Singh
Hossain, Safwan
Ling, Huan
McLean, Carson
Roewer-Despres, Francois
Skreta, Marta
Wen, Ethan
Yasodhara, Angeline
Young, Adamo
Yu, Geoffrey
Electrical and Computer Engineering
Emara, Salma Shukry
Fu, Yan
Tan, Xiaodan
Mechanical and Industrial Engineering
Crowson, Mathew
Dworakowski, Daniel
Statistical Sciences
Kogan, Ilan
Veitch, David
Management Analytics
Liu , Zhengyuan
Liu, Ziyue
Mielnik, Dominique
Rowe, Matthew
Wang, Ariel
Computer Science
Wang, Houze
Wu, KaiWen
Statistics (Data Science Specialization)
Bender, Travis
Li, Aileen
Systems Design Engineering Dulhanty, Christopher
Business Analytics
Chen, Dezhong
Morton, Evan
Computer Science (AI) Rajshree, Daulatabad

Spotlight on Scholarship Recipients:

Chris Dulhanty
2018-19 Vector Scholarship in AI Recipient
University of Waterloo, MASc, Systems Design Engineering
Previous Degree: B.Eng, Biomedical Engineering (University of Guelph)

How my research will have an impact: My research interests lie in the social impact of artificial intelligence with projects on auditing training datasets for representational bias, benchmark datasets for evaluation bias and on fairness and privacy implications of face recognition.

Jun Gao
2018-19 Vector Scholarship in AI Recipient
University of Toronto, MSc, Computer Science
Previous Degree: BSc, Computer Science (Peking University)

What are you working on now? In 2019, I was published in three different conferences: CVPR on interactive object segmentation, ICLR on analyzing representations in language modelling and NeurIPS on differentiable rendering and trying to learn 3D shapes from 2D images. My goal is to get into all the computer vision conferences, including ECCV and ICCV in the next year. I also work part-time as an intern at NVIDIA, where I get to learn more about graphics, 3D and AI in that domain.

Diana Lucaci
2018-19 Vector Scholarship in AI Recipient
University of Ottawa, MSc in Computer Science, Applied AI Concentration
Previous Degree: BSc, Computer Science (Alexandru Ioan Cuza University of Iasi)

How my research will have an impact: My thesis will be focused on the explainability of NLP algorithms. We have to keep an eye on the applicability of research in industry and work to eliminate the gap between pure research and specific applications. My thesis has the potential to touch so many industry applications including the medical domain, when AI agents are supporting the decision making process for specialists and doctors.

Maral Rasoolijaberi
2019-20 Vector Scholarship in AI Recipient
University of Waterloo, MASc in Systems Design Engineering
Previous Degree: BASc in Electrical, Electronics and Communications Engineering (Amirkabir University of Technology, Tehran Polytechnic)

What are you working on now? I’m currently working on a project to analyze histopathology images by applying U-Net, a convolutional neural network for biomedical applications, to segment tissue and remove background information. We will also compare this tool against other image processing tools as well to find out which method is more accurate or faster. So far, no one has used U-net for segmenting tissue. This application will have implications for cancer detection in the future, which is so inspirational and I am excited about.

Amrit Sehdev
2019-20 Vector Scholarship in AI Recipient
Queen’s University (Smith), Master of Management in Artificial Intelligence
Previous Degrees: Doctor of Medicine (University of Calgary); Master of Public Health (Queen’s University)

What’s next? As a physician, I’m lucky to work with colleagues and patients who continue to strive for better outcomes. We are working on NLP and Image Detection solutions currently to solve health system demand problems on a global scale. In the future, I hope to continue to combine my experience in healthcare and AI to work with like-minded people to solve problems and develop great solutions.

Scholarship Eligibility & Nomination Process

INFORMATION FOR STUDENTS

Nomination Process:

  • Nomination period opens: January 4, 2021
  • Prepare documentation and contact the institution to which you have applied: January to early March 2021
    • Students cannot directly apply to the Vector Institute for the scholarship. You are encouraged to work with the Ontario university to which you have applied to be nominated. 
    • Universities will also have specific internal deadlines related to the scholarship which will be earlier than Vector’s final submission deadline.
  • Deadline for submission: March 24, 2021 at 4 pm (EST)

Eligibility Criteria:

  • Entering a full-time master’s program in an AI-related field at an Ontario university for the 2021-22 academic year. The program must be Vector-recognized or you must be pursuing an individualized study plan that is demonstrably AI-focused.
  • Hold first-class standing (minimum of A- or equivalent) in the last two years of full-time equivalent study from a recognized university (typically 20 half-courses). Students’ transcripts should reflect preparedness for the proposed master’s program.
  • Consideration will be given to nominees with upper second class standing (B+) and relevant work experience, only if rationale for consideration is     included in the nomination package

Nomination Package Requirements:

Prospective students must  include all the following components in their nomination package to be considered:

  • Copies of all up-to-date transcripts (undergraduate and graduate, if applicable);
    • Students who submit unofficial transcripts will be required to submit official transcripts, should they be selected as scholarship recipients
  • Two references using the Referee Form (available January 2021), at least one of which is academic; 
  • An up-to-date one to two-page CV;
  • A 250-word statement outlining your reason for pursuing a master’s in AI, relevant AI-related experience, and career aspirations (suggested template available January 2021);
  • Self-Identification Form (available January 2021);
  • If not enrolled in a Vector-recognized program, an approved study plan including a course list and a description of thesis/capstone project (suggested template available January 2021).
  • If your GPA in the last two years of study is below A-, rationale for consideration of your nomination (i.e. describing extenuating circumstances)

Scholarship Conditions:

  • The scholarship is non-transferable, as selected recipients are required to register at the Ontario university and program they were nominated to receive the award for. 
  • The scholarship funds will be provided directly to the university to disburse to recipients.

FAQ for Students

Can candidates apply directly for a Vector Scholarship in Artificial Intelligence?

Programs can nominate eligible candidates who will or who have received an offer of admission. Candidates cannot apply directly for a Vector Scholarship in Artificial Intelligence. However, to support the nomination, candidates must supply a short statement, CV and solicit two referee reports to be sent directly to the program(s) to which the candidate is applying. Prospective students should alert the program of their interest in being nominated for a Vector Scholarship in Artificial Intelligence.

I am currently a master’s student studying in an AI-related field. Am I eligible to apply or to be nominated?

No, these are entrance scholarships for AI-related master’s students who will register and begin their studies in the 2020-21 academic year; others are not eligible.

I have applied to a master’s program in a Canadian university outside of Ontario. Can I be nominated for a Vector Scholarship in Artificial Intelligence?

No, the scholarships are restricted to AI master’s students studying at an Ontario university.

If I am awarded a scholarship and decide to accept an offer of admission in a different master’s program, can I keep the scholarship?

No, the scholarship is awarded to the candidate for study in the master’s program that submitted the nomination; it cannot be transferred to another program of study or to a similar program at a different university.

If I am selected to receive a Vector Scholarship in Artificial Intelligence and have accepted either a Tri-Council award (CGS-M) or an Ontario Graduate Scholarship (OGS), can I accept the Vector Scholarship in Artificial Intelligence ?

Yes, you can hold a Vector Scholarship in Artificial Intelligence and an OGS or CGS-M simultaneously.

If I am selected to receive a Vector Scholarship in Artificial Intelligence and I accept the award, can I defer my start date?

Usually, the Vector Scholarship in Artificial Intelligence must be taken up in accordance with the start date indicated by the program which nominated you. However, in extenuating circumstances (e.g. unanticipated: medical issues, family responsibilities, or visa delays), deferral may be granted with relevant documentation.

INFORMATION FOR ONTARIO MASTER’S PROGRAM ADMINISTRATORS & FACULTY

The combined support of the Province of Ontario and a commitment from Ontario’s universities to recruit top talent and increase the number of graduates from AI-related master’s programs are contributing to a robust AI ecosystem. The merit-based Vector Scholarships in Artificial Intelligence assist universities in attracting excellent students from Ontario and around the world and deepening the pool of applicants. In addition, the scholarship supports students in their pursuit of AI-related studies while building community among scholars.

Up to 115 Vector Scholarships in Artificial Intelligence will be awarded in 2021-22, each valued at $17,500 for one year (prorated for programs less than 12 months in duration).

Nomination Process & Eligibility Requirements:

Ontario university programs are invited to nominate their top applicants for the Vector Scholarship in Artificial Intelligence. Vector Institute does not accept applications directly from prospective students.

Key Dates:

  • Nomination period opens: January 4, 2021
    • All forms and templates will be made available at this time
  • Compile nomination packages and set internal deadlines: January to early March 2021 
  • Deadline for submission: March 24, 2021 at 4 pm (EST)
    • Programs are required to compile and review all nomination packages, rank their nominees, and calculate the GPAs of students in their last 2 years of study (typically 20 half-courses).

Eligibility Criteria for Nominees:

  • Has applied for entrance to a master’s program in an AI-related field or plan of study at an Ontario university for the 2021-22 academic year
  • Hold first-class standing (minimum of A- or equivalent) in their last two years of study (full-time equivalent, or last 20 half-courses) from a recognized university
    • Consideration will be given to candidates with upper second class standing (B+) and relevant work experience, or where extenuating circumstances apply, only if a rationale is provided in the nomination package

Program administrators should ensure that the following components are included in each nomination package:

  • Copies of all up-to-date transcripts with the corresponding grading system (both undergraduate, and if applicable, graduate transcripts)
  • Two referee forms, at least one of which is academic (available January 2021)
  • An up-to-date one to two-page CV
  • A 250-word statement outlining their reason for pursuing a master’s in AI, relevant AI-related experience, and career aspirations (suggested template available January 2021)
  • Self-Identification Questionnaire (available January 2021)
  • If not enrolled in a recognized program, an approved study plan including a course list and a description of thesis/capstone project (suggested template available January 2021).
  • If the nominee’s GPA in the last two years of study is below A-, rationale for consideration of the nomination (i.e. describing extenuating circumstances)

FAQ for Program Administrators & Faculty

How can programs help promote the Vector Scholarship in Artificial Intelligence?

The scholarship is intended to attract strong applicants and students to your program; as such, making applicants and prospective applicants aware of these awards is important. Easy to share marketing collateral on the scholarship has been distributed to programs. If your program would like this material, kindly email aimasters@vectorinstitute.ai.

Can candidates apply directly for a Vector Scholarship in Artificial Intelligence ?

No, programs can nominate eligible candidates who are eligible for admission or have received an offer of admission. Candidates cannot apply directly for a Vector Scholarship in Artificial Intelligence. However, to support the nomination, candidates must supply a short statement, a 1 to 2 page CV, and solicit two referee reports to be sent directly to the program(s) in which the candidate has applied. Prospective students may alert the program of their interest in being nominated for a Vector Scholarship in AI. In addition, the program can solicit top applicants to complete the requisite documentation for the scholarship application.

Can current master’s students studying in an AI-related field be nominated for a Vector Scholarship in Artificial Intelligence ?

No, these are entrance scholarship for AI-related master’s students who will register and begin their studies in the 2020-21 academic year; others are not eligible.

Can international applicants to an Ontario University be nominated for a Vector Scholarship in Artificial Intelligence?

Yes, providing they meet all the eligibility requirements and are highly qualified to merit nomination by the intended program of study.

How can programs support the Vector Scholarship in Artificial Intelligence process?

Programs are responsible for nominating incoming AI master’s students. This involves:

  1. Ensuring that eligible applicants to your program have been instructed to provide their 250-word statement, a 1 to 2 page CV, and seek references from two referees using the referee report form which will be made available January 6, 2020.
  2. Providing the prospective student with the name and email address of your program contact and the deadline date by which the contact must receive the statement, CV (if not included in your application) and referee reports (as per #1);
  3. Ensure that the deadline for submission of material is far enough in advance of Vector’s submission deadline of April 3, 2020 to allow for the ranking of nominees and the collation of the nomination package; and
  4. Complete and submit the appropriate nomination forms (available starting January 6, 2020) along with the nomination package. Full instructions on the nomination package will be made available on January 6, 2020.
If a student nominated by my program is awarded a scholarship and then decides to accept an offer of admission into a different master’s program, can they keep the scholarship?

No, the scholarship is awarded to the candidate for study in the master’s program that submitted the nomination; it cannot be transferred to another program of study in either the same university or a different university. In such cases, the scholarship reverts to Vector for possible re-allocation.

Can a Vector Scholarship in Artificial Intelligence recipient simultaneously hold a Tri-Council award (CGS-M) or an Ontario Graduate Scholarship (OGS)?

Yes, a Vector Scholarship recipient may hold an OGS or a CGS-M at the same time.

Can a Vector Scholarship in Artificial Intelligence recipient defer their start date?

Usually, the Vector Scholarship in Artificial Intelligence must be taken up in accordance with the start date specified on the nomination form. However, in extenuating circumstances (e.g. unanticipated: medical issues, family responsibilities, or visa delays), deferral may be granted with relevant documentation.

Are Vector Scholarships in Artificial Intelligence paid directly to the recipient?

Funds are transferred to the universities and paid out through the Faculty/School of Graduate Studies student awards system in instalments. All funds go directly to and in full to the recipients, providing they maintain full-time enrolment and are in good standing.

I am using a Mac computer and experiencing issues with merging nomination packages for students. What should I do?

We strongly recommend the use of Mac Preview in compiling nomination packages, as there have been errors documented with using Adobe and other platforms for merging PDFs.

CAREER OPPORTUNITIES AND SUPPORTS FOR MASTER’S STUDENTS AND ALUMNI

Vector Digital Talent Hub

Students and alumni* have access to Vector’s Digital Talent Hub. Users can browse and apply to AI job postings, set up automated job alerts, and upload their profile details for employers to contact them regarding career opportunities. Students and alumni* are welcome to Create a Profile.

Career Supports for Students

Vector-affiliated students and alumni* enjoy access to career development and networking activities. These opportunities enable students to explore various career paths in AI, better understand the opportunities and challenges of AI adoption across different sectors, and meet with potential employers. Sign up to learn about events and more!

*including students and graduates from Vector-recognized programs, recipients of the Vector Scholarship in Artificial Intelligence, as well as  researchers affiliated with Vector Faculty Members and Faculty Affiliates.

Careers in AI events are held across the province including Kitchener and Ottawa, where experienced industry professionals working in the local AI ecosystems share about opportunities and challenges in today’s AI industry and master’s students have the opportunity to network and connect with their peers in AI programs. Pictured on the right: Melissa Judd (Vector Institute), Maria Pospelova (Interset), Mike Cloutier (Accenture), Robin Grosset (Mindbridge Analytics Inc.) and Nevena Francetic (Shopify Inc.)

AI Master’s Summit & Career Fair (September 2019, Toronto): At this inaugural event, over 300 master’s students from 30 programs across Ontario had the opportunity to meet with 18 of Vector’s sponsors to learn more about career opportunities in AI and make meaningful connections with one another. Photographer: Calyssa Lorraine

SEEKING PROGRAM RECOGNITION

The Vector Institute has been tasked with supporting Ontario’s growing AI eco-system including the goal of accelerating the number of artificial intelligence (AI)-related master’s graduates. To achieve this goal, universities with expertise in AI-related areas are invited to expand or enhance relevant existing master’s programs or create new AI-related programs to:

  1. Meet the essential requirements articulated by Vector for core technical AI and complementary AI-related fields; and
  2. Prepare highly qualified graduates who demonstrate area-specific advanced knowledge, skills and competencies sought by the AI-sector to build a highly skilled workforce and support economic growth and productivity.

Programs must prepare graduates to meet all essential requirements as well as advanced AI field specific learning outcomes. The Vector Institute Guidance Document for AI-Related Master’s programs details both the process and requirements for program recognition. Programs are invited to complete the Program Recognition Submission form to be considered for recognition. While submissions for Vector recognition can be made at any time, the following are the scheduled meeting dates of the Program Recognition Panel for the 2020-21 academic year:

  • November 3, 2020
  • February 3, 2021
  • May 5, 2021

Benefits of Program Recognition

Programs recognized by Vector will be listed on our website as Vector recognized master’s programs. Programs may highlight that they have been recognized by the Vector Institute as delivering a curriculum that equips graduates with the skills and competencies sought by industry.

Students enrolled in recognized programs can take advantage of:

  • Career development & supports such as the Vector AI Master’s Summit & Career Fair, where students meet with like-minded peers from across Ontario and interact with potential employers that are building AI teams and adopting the technology across their organizations.
  • Opportunities to connect with Vector industry sponsors, who are at the forefront of AI in Canada through education and networking events hosted by the Vector Institute, such as the Careers in AI Panel.
  • Access to internships and full-time roles through the Vector AI Digital Talent Hub featuring AI-related opportunities.
  • Exposure to the latest AI research from around the globe through events such as:
  • Opportunities to engage with other students and alumni in AI master’s programs across Ontario, both on and off-line.

VECTOR-RECOGNIZED AI MASTER’S PROGRAMS

Master of Science/Master of Applied Science (collaborative specialization in AI)

The University of Guelph’s Collaborative Specialization in Artificial Intelligence (AI) provides thesis-based master’s students in Computer Science, Engineering, Mathematics and Statistics, and Bioinformatics with a diverse and comprehensive knowledge base in AI. Students will learn from a multidisciplinary team of faculty with expertise in fundamental and applied deep learning and machine learning, while conducting AI-related research guided by a faculty supervisor. Through a combination of online learning, lectures, team-based problem-solving, and experiential learning opportunities, students will obtain broad expertise in machine learning and AI. They will gain essential skills in programming and algorithmic thinking, mathematical foundations and statistical analysis for AI, optimization, and data visualization. Additionally, graduates will have a deep understanding about the policy, regulatory and ethical issues related to AI.

By the end of this program, graduates will have comprehensive understanding of leading-edge AI techniques and will be able to apply this knowledge to solve real-world problems. Graduates will find employment opportunities in government and private industry, filling in-demand jobs such as machine learning research scientists, consultants, data scientists, and software engineers.

Master of Science (Computer Science – AI)

The Department of Computer Science is offering a two-year, thesis-based Master of Science in Computer Science (MSc) program with a specialization in Artificial Intelligence (AI).
Students will develop the skills and knowledge to conduct research in the field of Computer Science with a focus on core AI techniques. Upon completion, students will be able to apply and select appropriate AI algorithms and techniques in a variety of industrial sectors and further advance the AI related research. Topics will include natural language processing, deep learning, machine learning, image processing, pattern recognition and other emerging technologies. Finally, students will develop research and application based ethical awareness.

Master of IT Security (Artificial Intelligence Security)

Ontario Tech University offers a specialized field within its Master of IT Security program with a focus on Applications of Artificial Intelligence in IT Security (MITS-AIS). This professional stream is the first of its kind in Canada and combines a deep knowledge of IT Security with hands-on knowledge of artificial intelligence systems and machine learning, and provides students with a comprehensive understanding of the applications of this technology. Most courses in the MITS and MITS-AIS program include hands-on and laboratory assignments that simulate a variety of computer networking, security attacks and defence scenarios.

Students must complete 30 credits, including six mandatory and two elective courses in AI and IT Security; a seminar course; and the option of either a Capstone project to conduct research on a topic related to AI and security under the supervision of a faculty member, or an industry internship; subject to availability and program director’s approval.

Graduates of this program can seek employment in the growing artificial intelligence industry, public and private organizations, as well as IT security firms.

University of Ottawa / Université d’Ottawa

Master of Computer Science (Applied AI)

The applied artificial intelligence (AI) concentration within the existing Master of Computer Science program at uOttawa encompasses both the foundations and applications of machine learning. This unique program emphasizes the application of machine learning and AI to solve problems in areas such as health care, medicine, education, manufacturing and cyberspace.

Courses include machine learning and other AI-related topics such as deep learning, reinforcement learning, natural-language processing, computer vision, semantic web and intelligent physical systems. The program also includes a seminar,  that centres on the ethical and societal impact of AI, while fostering community building and strengthening students’ communication skills.

Students will become experts in AI-related algorithms and methodologies, and will acquire knowledge to manage, assess and explore a variety of data across multiple application areas. Students will further gain an understanding of the potential of bias in AI technologies, the ethics, benefits and dangers of AI, and the impact of AI on society. These are scarce competencies that are immediately useful and valued by industry, as well as academia.

Le programme en intelligence artificielle (IA) appliquée du programme de maîtrise en informatique de l’uOttawa couvre tant les aspects fondamentaux que les applications liées à l’apprentissage automatique. Ce programme unique met l’accent sur la résolution de problèmes concrets liés aux soins de la santé, la médecine, l’éducation, l’industrie manufacturière et le cyberespace.

Les cours portent sur l’apprentissage profond, l’apprentissage par renforcement, le traitement automatique des langues, la vision artificielle, le web sémantique et les systèmes intelligents. Ce programme comprend aussi des séminaires portants sur les aspects éthiques et sociaux de l’IA.

Les étudiants poursuivant la concentration en IA deviendront des experts en algorithmes et méthodologies d’apprentissage automatique et posséderont les connaissances nécessaires pour gérer, évaluer et explorer une variété de données dans de multiples domaines d’application. Ils acquerront une compréhension du risque de biais dans l’apprentissage machine et d’autres technologies d’IA, ainsi que l’éthique, les avantages et les dangers de l’IA, et l’impact de l’IA sur la société. Il s’agit de compétences rares qui sont très appréciées tant par l’industrie que par le milieu universitaire.

Master of Applied Science (MASc) in Electrical and Computer Engineering and Master of Engineering (M.Eng) in Electrical and Computer Engineering  — Applied Artificial Intelligence Concentration

The objective of this  program is to graduate highly qualified electrical and computer engineers who not only are highly skilled in AI theory, but are also equipped with the desired skills to apply their knowledge across multiple domains. To this end, it covers both the fundamental knowledge in machine learning and its applications to the problems in electrical and computer engineering. Furthermore, this program leverages the application of machine learning and AI to innovate in areas such as communications, devices, utilities, transportation, digital health, cybersecurity and manufacturing.

MASc students complete a thesis, while M.Eng. students complete a project.  Both are eligible for and encouraged to do an industry internship.  The course on social implications and ethics equips students with effective oral and written communications skills to communicate with generalist audiences and clients.  The program ensures students are able to develop and present AI-based solutions, and apply AI-based methodologies to solve practical problems in electrical and computer engineering.  These include topics such as robotics, digital health, cyber-physical systems, wired/wireless communications, cyber-security and multimedia systems.  As well, the students work with professionals from other disciplines to integrate AI-based solutions into services and products in other domains.

Maîtrise ès sciences appliquées Génie électrique et génie informatique (M.Sc.A), Maîtrise en ingénierie Génie électrique et génie informatique (M.Ing) – Concentration en intelligence artificielle appliquée

L’objectif de ce programme est de former des ingénieurs électriciens et informaticiens hautement qualifiés en théorie de l’intelligence artificielle (IA) et dotés des compétences requises pour appliquer leurs connaissances à plusieurs domaines. À cette fin, ce programme couvre à la fois les connaissances fondamentales en apprentissage automatique et ses applications aux problèmes d’ingénierie électrique et informatique. En outre, ce programme exploite l’application de l’apprentissage automatique et de l’IA pour innover dans des domaines tels que les communications, les dispositifs, les services publics, les transports, la santé numérique, la cybersécurité et la fabrication.

Les étudiants à la M.Sc.A. doivent compléter une thèse tandis que ceux à la M.Ing. doivent compléter un projet.  Tous les étudiants peuvent s’inscrire à un stage en industrie, une option fortement encouragée.  Le cours sur les implications sociales  et l’éthique dans la conception, l’IA et la robotique fournit aux étudiants des expériences de communication orale et écrite, les préparant aux scommunication auprès de clients et du grand public.  Le programme procure aux étudiants les habiletés et connaissances nécessaires au développement et à la présentation de solutions fondées sur l’IA pour des domaines du génie électrique et informatique tels que la robotique, les services de santé numériques, les systèmes cyber-physiques, les communications avec et sans fil, la cybersécurité et les systèmes multimédias. De plus, les étudiants travaillent avec des professionnels d’autres disciplines pour intégrer des solutions fondées sur l’IA à des services et produits d’autres domaines.

Queen’s University (Smith School of Business)

Master of Management in Artificial Intelligence

Harnessing AI’s potential for competitive performance requires a new type of professional: one who not only understands the capacity of the science but has the expertise to apply it to organizational needs and strategies, and who can navigate the ethical, economic and societal implications. The Master of Management in Artificial Intelligence will provide:

  • A strong understanding of the technical principles of AI and modern methods for data search and retrieval, and how to practically apply them to real world problems;
  • Command of best practices in identifying opportunities for and applying AI;
  • Expertise in the business practices required to effectively use AI and machine learning;
  • Awareness and engagement in the ethical, economic, and societal impacts of computers exhibiting intelligent behavior;
  • Enhancement of skills for communicating complex problems and AI solutions to wide audiences in an organization; and
  • Training in creating and maintaining high performance work teams.

Master of Management Analytics; Global Master of Management Analytics

The Master of Management Analytics – Toronto marries training in core data analytics concepts and tools, with outstanding education in business strategy and management. It includes extensive review of the fundamental mathematical and statistical theories and methods that underlie modern analytics, but with a practitioner focus. The program features some of the best management educators in the world, plus industry specialists and practitioners who bring their daily experience and insights to the discussion. Students will be exposed to a variety of tools and programming languages including R, Python, Tableau, Hadoop, and Spark, and technical courses are taught by experts and range from importing data and data visualization to machine learning, deep learning, and more. Take this 12-month program while working, with classes based at Smith Toronto, a dedicated learning facility in downtown Toronto.

Master of Science (Computer Science, AI)

The Queen’s School of Computing offers a Field of Study in AI that prepares students for AI-related work in leading technology firms, healthcare companies, automobile manufacturers, and research labs.

Students take five graduate courses and complete an AI-related MSc thesis over a period of 18 to 24 months.  Upon graduation, students will have a solid background in core AI with a “Field of Study in AI” credential on their transcript.

The MSc thesis gives the student experience delving deep into a single AI problem in either core AI or an application of AI. The thesis typically provides training in project definition, substantial implementation, the use of real-world AI tools and packages, and technical writing.

Students can select from AI courses among deep learning, reinforcement learning, data mining, neural networks, nonlinear optimization, and pattern recognition. Students also take a research methods and AI-in-society course and may choose a non-AI course as part of the program.

Master of Applied Science (Electrical and Computer Engineering, Field of Study in AI

The Department of Electrical and Computer Engineering at Queen’s offers a unique Master of Applied Science program with a Field of Study in Artificial Intelligence (AI) that provides the graduate students with a solid foundation in the principles of AI, machine learning and deep learning. Graduates will be able to design and analyze AI-related algorithms and methodologies, employ modern scientific and engineering tools, and apply AI-based techniques to tackle complex research problems. They will acquire advanced research and technical knowledge in AI-related fields and will have deep understanding about the ethical and societal implications of AI.

The Department has substantial expertise in AI-related methodologies and application areas. The program will prepare graduates through a combination of classroom and online learning, team-based problem-solving and course projects, research seminars, and faculty-supervised research projects. A broad range of courses allow students to tailor their education according to career goals. The program, with its mixture of AI-related methodologies and application areas, prepares highly-qualified graduates with area-specific knowledge, skills, and competences highly sought by the public and private AI sector.

Master of Engineering (Electrical, Computer and Biomedical Engineering, AI)

Ryerson University’s Department of Electrical, Computer and Biomedical Engineering Master of Engineering program (MEng) with an AI concentration will provide students with the essential training to be successful professionals in the field of AI. Students will be required to take four core courses: 1) Intelligent Systems, 2) Neural Networks, 3) Deep Learning, and 4) Advanced Data Engineering. Four interdisciplinary electives will also be required in application areas such as energy, sustainability, computer networks, and digital media—which will be studied through an AI lens. At the core of the program, the students will study ethical and societal implications of AI, covering topics such as bias, fairness and accountability. One of Ryerson’s strengths is combining theory with experiential learning; as such, a practicum will present students with the opportunity to solve a real-world problem using AI. Upon completion of the program, our graduates will be able to identity the requirements of an AI-driven system, analyze state-of-the-art AI techniques and apply them in a range of disciplines to solve some of industry and society’s greatest challenges.

Master of Science in Data Science and Analytics

This unique one-year Master of Science (MSc) degree program enables students to develop interdisciplinary skills and gain a deep understanding of technical and applied knowledge in data science and analytics. Graduates are highly trained, qualified data scientists who can pursue careers in industry, government or research. Core technical skills such as math, statistics, operations research, programming, machine learning and domain knowledge are the core competencies that are in greatest demand in the marketplace. The program is designed to meet the requirements of the marketplace. Data science is an interdisciplinary field that combines expertise from different technical and expert domains. The program is designed with the contributions of four different faculties to reflect the interdisciplinary nature of the field. The curriculum consists of six courses and a mandatory applied advanced project.

Students learn how data science and analytics can help to improve decisions throughout an organization’s value chain, understand how recommendations lead to tangible actions through prescriptive analytics techniques, gain a good understanding of methods used in building such data-driven models, and acquire hands-on experience with machine learning algorithms that are widely used in practice.

University of Toronto (Rotman School of Management)

Master of Management Analytics

The Rotman Master of Management Analytics (MMA) is a nine-month, full-time program running from August to April. The program is focused on teaching the applications of advanced analytics, AI, and machine learning to provide data-driven insights on complex managerial problems. Balancing rigorous theoretical knowledge with experiential learning opportunities, the program is structured to first develop tools and techniques, and then focus on the holistic application of analytics and AI to problems arising in various areas of management. Hands-on skills, including coding and knowledge of advanced analytic tools are emphasized, as are effective communication and presentation skills. Two unique features of the program are the Analytics Colloquia, consisting of modules ranging from Ethics in AI to Applications of Quantum Computing, and the Management Analytics Practicum, where students work on a real-world business problem over the course of a nine-month project. The practicum projects in 2018/19 reflect broad-based interest and come from a wide cross-section of industries including Banking, Pharmaceutical, Telecommunications, Insurance, Retail, and Services.

University of Toronto (Institute of Health Policy, Management and Evaluation)

Master of Health Informatics

The Master of Health Informatics (MHI) is a professional program enabling graduates to harness the potential of data and knowledge for the better management of health and care. Set within University of Toronto’s Dalla Lana School of Public Health, and the Institute of Health Policy, Management and Evaluation, MHI exists within a vibrant, interdisciplinary culture. Taught by health sector leaders, MHI focuses on upstream development of the healthcare complement in areas of policy, management and evaluation to prepare students to lead AI-based change. By design, each cohort reflects healthcare’s many stakeholders, and team-based learning draws together students from clinical, analytic, business, project management and technological backgrounds. MHI is a 16-month full-time program that includes a 4-month applied professional practicum and an AI-based capstone project. The Executive MHI is a modular stream enabling students to balance full-time employment and study. MHI graduates bridge complex social, cultural, political and technological settings in healthcare. With competencies in responsible innovation and knowledge-based implementation, graduates are ready to bring judgement and order to the process of assimilating AI and related knowledge into healthcare.

Master of Data Science and Artificial Intelligence

Students in the Master of Data Science and Artificial Intelligence at Waterloo receive an in-depth education in the theory and practice of machine learning and computational analysis of massive data sets plus industrial experience. Offered jointly by three departments (Computer Science, Statistics and Actuarial Science, and Combinatorics & Optimization), available courses cover robust and efficient storage systems of massive data, effective statistical data exploration, and algorithms for discovering hidden structures. The program typically requires three terms on campus (to complete nine courses) and one term in an industrial co-op placement, for a total of 16 months. Waterloo’s mature and extensive co-operative education system and industrial ties give students opportunities to work at top data science and AI companies in North America. Entering students should have a bachelor’s degree in computer science, statistics, data science, or a related mathematical field. Background courses are available during the first term for students missing an aspect of the prerequisites.

Master of Mathematics in Data Science

Students in the Master of Mathematics in Data Science program at Waterloo work at the forefront of modern research in topics related to data science, encompassing statistics, computer science, and optimization. Degree requirements include the completion of four graduate courses and the writing of a Master’s thesis under the supervision of a leading expert from one of three departments (Computer Science, Statistics and Actuarial Science, and Combinatorics & Optimization) that participate in the program. The program requires 4-6 terms, i.e., up to two calendar years. The course requirements include data exploration, distributed computing with data, machine learning and optimization, and a fourth elective course. Students in this program receive financial support composed of research and teaching assistantships and scholarships. Entering students should have a bachelor’s degree in computer science, statistics, data science, or a related mathematical field. Background courses (not counting toward the degree) are available for students missing an aspect of the prerequisites.

Master of Mathematics (Computer Science) & Master of Mathematics (Statistics), Data Science Specializations, which are no longer offered, were also Vector recognized programs.

Master of Data Analytics (Artificial Intelligence)

Western’s Master of Data Analytics in Artificial Intelligence is a one-year professional science master’s program designed to produce technical data analytics professionals skilled in artificial intelligence, machine and deep learning, big data management and analysis infrastructure for unstructured data as well as other foundational areas of analytics, including visualization, databases, data carpentry and statistical modelling and inference, who are also effective communicators with complementary business skills and teamwork experience. The fall and winter curriculum consist of courses that focus on fundamental data analytics and AI-specific methods and their applications, along with a seminar series in the ethics and societal implications of AI. These courses are commonly taught by faculty who develop and apply data analytics and data science methods in their research. A career development seminar also runs over the fall and winter terms, providing students with the skills to successfully chart an effective course for their career. The summer term consists of an Experiential Learning Opportunity where students gain valuable practical experience using the analytics skills they have developed in a workplace environment.

Master of Computer Science and Electrical and Computer Engineering (collaborative specialization artificial intelligence)

Western University’s departments of Computer Science (CS) and Electrical and Computer Engineering (ECE) are jointly offering a collaborative specialization artificial intelligence (CSAI) concentration in existing Master programs in CS and ECE (i.e., MSc, MESc and MEng).  CSAI enhances the education and research of a graduate student by adding a module to their program of study. The concentration is designed so that graduates have a solid foundation in artificial intelligence methodologies, enabling technologies that include big data computational platforms, data management systems, and GPU programming as well as social and ethical challenges/limitations/advantages of AI.   A student in the program must demonstrate their mastery of artificial intelligence with an AI-related thesis, project or internship.  The CSAI program, with its mixture of theoretical and hands-on training will provide graduate students with the quality experience necessary to prepare them for careers in high-tech Canadian industries.

Master of Science in Computer Science- Artificial Intelligence [with/without Co-Operative Education]

The concentration in Artificial Intelligence is part of the thesis-based program of the Master of Science in Computer Science at the University of Windsor, and has a curriculum that includes a variety of AI and AI-related courses in specialized areas of computing technology, applications, and theory. The program introduces students to advanced topics in AI and AI-related subjects and applications, as well as to new AI technologies that are in high demand for computer professionals in the IT industry. The topics included in the AI stream cover the fundamental concepts of AI, concepts related to AI, as well as important applications of AI. Students graduating from the AI stream will not only be able to make contributions in the AI software industry as other non-streamed students, but also be ready for the new challenges to help Ontario’s growing AI ecosystem or to help advance AI and its related fields in their PhD studies. By the end of this program, graduates will have a comprehensive understanding of leading-edge AI techniques and will be able to apply this knowledge to solve real-world problems. Graduates will find employment opportunities in government and private industry, filling in-demand jobs such as machine learning scientists, consultants, data scientists, and software engineers.

Master of Science (Computer Science, AI)

York University’s Master of Science in Computer Science program with specialization in AI has been strategically designed to provide its graduates with a solid grasp of the computational framework underlying AI methodologies with hands-on experience on how they are applied to diverse computing problems. The core coursework focuses on fundamentals of AI, machine learning theory, data mining, and ethics of AI. A broad range of elective courses that focus on applications of AI in areas such as computer vision, robotics, neural networks & deep learning, natural language processing and data mining & analytics provide students with the ability to tailor their education according to career goals. Under the supervision of a faculty member with expertise in AI, the completion of a research project gives graduates a competitive advantage by leveraging York University’s partnerships to gain coveted industry experience. With this knowledge, graduates are positioned to successfully deploy AI methodologies across many sectors.

Master of Business Analytics

The Master of Business Analytics (MBAN) offered by the Schulich School of Business is a professional degree program designed to provide students with the breadth and depth of knowledge to be successful in a wide range of careers in areas such as banking, insurance, marketing, consulting, supply chain management, healthcare, and technology. What makes the Schulich MBAN program unique is the combination of academic rigor and valuable practical experiences, made possible by a strong set of collaborative relationships with industry. World-class faculty, an advisory board composed of senior leaders from successful organizations (e.g., TD Bank, BMO, CIBC, Deloitte, TELUS, SAS, Rogers, Accenture, PWC, etc.), and project partnerships with dozens of client companies ensure that the program has remained at the cutting edge of the theory and practice of Artificial Intelligence. By the end of the program, graduates are able to apply business analytics and AI-supported techniques to generate concrete and actionable business solutions.

Master of Management in Artificial Intelligence (Schulich School of Business)

Artificial Intelligence (AI) is undergoing a landmark evolution, transforming the private and public sectors. As organizations adopt and invest in AI technology, a new style of management is needed – one that pairs a leader’s vision with a scientist’s mastery over a growing body of specialized knowledge. The 12-month Master of Management in Artificial Intelligence (MMAI) is designed to meet the growing need for talented professionals with the skills and advanced applied knowledge to develop, evaluate, refine and implement AI-related applications and technologies. The immersive curriculum offers a technical foundation in natural language processing, computational methods and modeling, paired with core business skills. Students will explore a critically evolving ethical landscape as they confront moral topics in AI, such as algorithmic bias, data privacy and intelligent agent autonomy. The capstone Artificial Intelligence Consulting Project (AICP) provides students with an opportunity to solve a significant business problem by designing an AI-centered approach. Working in the Deloitte Cognitive Analytics and Visualization Lab student teams will deliver a solution to a client organization, interacting with industry managers, technicians, suppliers and other stakeholders.

**

The Vector Scholarships in Artificial Intelligence, together with internships and networking programs, are a core component of the Vector Institute’s RAISE initiative, supported by the Province of Ontario, to develop and connect Ontario’s AI workforce to fuel AI-based economic development and job creation.

Scroll to Top