Collaborative Specialization in Artificial Intelligence (M.Sc./M.A.Sc.)

Collaborative Specialization in Artificial Intelligence

The University of Guelph’s Collaborative Specialization in Artificial Intelligence (CSAI) provides thesis-based master’s students with a diverse and comprehensive knowledge base in AI. Students 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 obtain broad expertise in machine learning and AI, including essential skills in programming and algorithmic thinking, mathematical foundations and statistical analysis for AI, optimization, and data visualization. Students also develop an intimate understanding about the policy, regulatory and ethical issues related to AI and its uses.

The CSAI program is a Vector-Institute affiliated program. Its students become part of the Vector Institute’s community of renowned researchers, major Canadian companies, and AI startups solving high-impact problems.


Vector Institute Affiliation

Vector Institute Logo

Vector Scholarship in Artificial Intelligence

Students who are enrolled in the University of Guelph Collaborative Specialization in Artificial Intelligence are eligible to apply for Vector Scholarships in Artificial Intelligence, valued at $17,500 each. Both domestic and international students with first class standing (minimum A- in their last two years of full-time study) are eligible for consideration. The 2021 nomination deadline runs from January 4, 2021 to March 24, 2021.

You can find more information at the Vector Institute website

Networking and Events

The Vector Institute’s exclusive events put you face-to-face with AI teams from major Canadian employers, providing unique access to career opportunities. Build relationships with a network of AI professionals that can become a spring of new opportunity, insight, and collaboration over your career.

Digital Talent Hub

Discover career opportunities in the Vector Institute’s extensive industry network through the Digital Talent Hub, an exclusive online platform that curates AI-related job openings among top Canadian employers. Available only to the Vector community, the Digital Talent Hub is trusted by hiring managers and connects talent with a wealth of high-impact internship and full-time openings at leading companies.


Meet our Students

Mostafa

Mostafa Elkurdy

Environmental Engineering (MASc), Collaborative Specialization in Artificial Intelligence

I really enjoyed my undergraduate experience at Guelph, which included multiple research co-op work terms. I was also especially interested in the Collaborative Specialization in Artificial Intelligence and my ability to integrate AI with my thesis in the field of Environmental Engineering.

My background in Environmental Engineering has lead me to pursue ways of improving our understanding of the complexities involved in environmental systems. Specifically, the goal of my research is to improve our understanding of flooding events, the specific mechanisms leading to these events, and the consequential impacts on human life and the surrounding environment. Read Mostafa's full story.

 

Alysha

Alysha Cooper

Statistics (MSc), Collaborative Specialization in Artificial Intelligence

With an increase in data, improving technology and computational power, artificial intelligence will continue to evolve and be an aid in many issues. Although the idea of artificial intelligence taking over can seem daunting to individuals, I believe that if different fields collaborate to make ethical algorithms, it will benefit society in ways we can’t even imagine right now. Particularly in healthcare, AI has the potential to be a powerful tool in diagnosis, caretaking, and risk predictions.

Statistics and artificial intelligence excite me because it is interesting how you can use them to understand the relationship between variables or even make predictions for other observations. I always found enjoyment in analyzing data to answer research questions. The analysis in research is the most exciting part since it is when you find out whether your hypothesis was correct or if there is something else that can be observed in the data. The more I learn about statistics and artificial intelligence, the more excited I get by the potential of it and how it can be used. Read Alysha's full story.


Program Details

Affiliated Programs (Thesis-Based)

  • Master of Applied Science in Engineering
  • Master of Science (MSc) in Bioinformatics
  • MSc in Computer Science
  • MSc in Mathematics and Statistics

Students We Attract

Top domestic and international students from undergraduate and graduate programs that include: Biostatistics; Computer Sciences; Computer, Electrical, Electronic, Environmental, Information Technology, Software, and Systems Engineering; Mathematics; and Physics.

Types of Careers

Graduates will be in-demand by government and private industry, for positions that include: machine learning researcher, computer vision engineer, data engineer, data scientist, software engineer, statistician.


Course List

Masters students in the collaborative specialization in artificial intelligence must complete the following:

  • UNIV*6080 Computational Thinking for Artificial Intelligence
  • UNIV*6090 Artificial Intelligence and Society

One of the following elective core courses:

  • CIS*6020 Artificial Intelligence
  • ENGG*6500 Introduction to Machine Learning
  • STAT*6801 Statistical Learning

Two of the following complementary AI-related courses:

  • BINF*6970 Statistical Bioinformatics
  • CIS*6050 Neural Networks
  • CIS*6060 Bioinformatics
  • CIS*6070 Discrete Optimization
  • CIS*6080 Genetic Algorithms
  • CIS*6100 Parallel Processing Architectures
  • CIS*6120 Uncertainty Reasoning in Knowledge Representation
  • CIS*6140 Software Engineering
  • CIS*6160 Multiagent Systems
  • CIS*6320 Image Processing Algorithms and Applications
  • CIS*6420 Soft Computing
  • ENGG*4460 Robotic Systems
  • ENGG*6090 Image Processing
  • ENGG*6100 Machine Vision
  • ENGG*6140 Optimization Techniques for Engineering
  • ENGG*6570 Advanced Soft Computing
  • MATH*6020 Scientific Computing
  • MATH*6021 Optimization I
  • MATH*6051 Mathematical Modelling
  • PHIL*6760 Science and Ethics
  • STAT*4000 Statistical Computing
  • STAT*6821 Multivariate Analysis
  • STAT*6841 Computational Statistical Inference

Click here for more information on course selection options according to home program.


Graduate Faculty

If you are interested in pursuing an AI-related master's thesis at the University of Guelph, then please contact one of the below-listed faculty members to see if your research interests align and to confirm if they are accepting students:

  • Sarah Adamowicz, Associate Professor, Integrative Biology, Bioinformatics Graduate Program
  • Ayesha Ali, Associate Professor, Mathematics and Statistics, Bioinformatics Graduate Program
  • Luiza Antonie, Assistant Professor, School of Computer Science
  • Shawki M Areibi, Professor, School of Engineering
  • Daniel Ashlock, Professor, Mathematics and Statistics, Bioinformatics Graduate Program
  • Christine Baes, Assistant Professor, Animal Biosciences, Bioinformatics Graduate Program
  • Mohammad Biglarbegian, Associate Professor, School of Engineering
  • Scott Brandon, Assistant Professor, School of Engineering
  • Neil Bruce, Associate Professor, School of Computer Science
  • David A Calvert, Associate Professor, School of Computer Science
  • Monica Cojocaru, Associate Professor, Mathematics and Statistics
  • Christopher Collier, Assistant Professor, School of Engineering
  • Rozita Dara, Assistant Professor, School of Computer Science
  • Fantahun Defersha, Associate Professor, School of Engineering
  • Ali Dehghantanha, Assistant Professor, School of Computer Science
  • Ibrahim Deiab, Associate Professor, School of Engineering
  • Bob Dony, Associate Professor, School of Engineering
  • Hermann Eberl, Professor, Mathematics and Statistics, Bioinformatics Graduate Program
  • Zeny Feng, Associate Professor, Mathematics and Statistics, Bioinformatics Graduate Program
  • David Flatla, Associate Professor, School of Computer Science
  • Andrew Gadsden, Associate Professor, School of Engineering
  • Bahram Gharabaghi, Professor, School of Engineering
  • Karen Gordon, Associate Professor, School of Engineering
  • Gary Grewal, Associate Professor, School of Computer Science
  • Andrew Hamilton-Wright, Associate Professor, School of Computer Science, Bioinformatics Graduate Program
  • Julie Horrocks, Professor, Mathematics and Statistics, Bioinformatics Graduate Program
  • Hadis Karimipour, Assistant Professor, School of Engineering
  • Stefan C Kremer, Professor, School of Computer Science, Bioinformatics Graduate Program
  • Anna Lawniczak, Professor, Mathematics and Statistics
  • Lei Lei, Associate Professor, School of Engineering
  • William Lubitz, Associate Professor, School of Engineering
  • Lewis Lukens, Associate Professor, Plant Agriculture, Bioinformatics Graduate Program
  • Pascal Matsakis, Professor, School of Computer Science
  • Ed McBean, Professor, School of Engineering
  • Medhat Moussa, Professor, School of Engineering
  • Khurram Nadeem, Assistant Professor, Mathematics and Statistics, Bioinformatics Graduate Program
  • Mihai Nica, Assistant Professor, Mathematics and Statistics
  • Charlie Obimbo, Associate Professor, School of Computer Science
  • Michele Oliver, Professor, School of Engineering
  • Stacey Scott, Associate Professor, School of Computer Science
  • Fei Song, Associate Professor, School of Computer Science
  • Petros Spachos, Assistant Professor, School of Engineering
  • Deborah A Stacey, Associate Professor, School of Computer Science
  • Graham Taylor, Associate Professor, School of Engineering, Bioinformatics Graduate Program
  • Dan Tulpan, Assistant Professor, Animal Biosciences, Bioinformatics Graduate Program
  • Eran Ukwatta, Assistant Professor, School of Engineering
  • Fangju Wang, Professor, School of Computer Science
  • Mark Wineberg, Associate Professor, School of Computer Science
  • Simon Yang, Professor, School of Engineering
  • Yang Xiang, Professor, School of Computer Science
  • Dirk Steinke, Adjunct Professor, Integrative Biology, Bioinformatics Graduate Program

Program Contacts

Program Director and Graduate Program Coordinator:
Graham Taylor

Please direct all inquiries to:
csaigrad@uoguelph.ca