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Master of Applied Science (MASc) with a Field of Study in Artificial Intelligence

The Master of Applied Science program with a Field of Study in Artificial Intelligence provides 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.

Program Overview

Advancement in computing technology and the availability of big data has led to a resurgence of research in artificial intelligence (AI), machine learning, and deep learning. AI is pushing the innovation boundaries across all disciplines, and industry has been investing heavily in various AI technologies. There is a high demand for graduates with an AI background from industry and research labs. The Department of Electrical and Computer Engineering (ECE) has substantial expertise in AI-related methodologies and application areas.

Program Structure

The program structure for the MASc program with a Field of Study in Artificial Intelligence is as follows:

• Take a minimum of two courses from the list of AI-related courses, one of which is the mandatory graduate course ELEC 825
• Take up to two more graduate courses as required in the MASc program
• Complete an AI-related MASc thesis
• Complete other requirements, including taking the graduate seminar course, ELEC 891, and the non-credit APSC 812 AI Ethics and Society course

AI-related Courses

• ELEC 823 Signal Processing
• ELEC 825 Machine Learning and Deep Learning
• ELEC 829 Optimization for Machine Learning
• ELEC 842 Safe Learning-Based Control for Robotics
• ELEC 872 Artificial Intelligence and Interactive Systems
• ELEC 874 Deep Learning in Computer Vision
• ELEC 877 AI for Cybersecurity
• ELEC 879 Wearable and loT Computing
• ELEC 880 Machine Learning for Natural Language Processing
• ELEC 888 Probabilistic Machine Learning

Faculty

The core ECE faculty delivering the curriculum components of the MASc with the field of study in AI are:

• Xiaodan Zhu: machine learning, deep learning, and natural language processing
• Ali Etemad: Machine learning, Internet of Things, data science
• Michael Greenspan: Machine vision, image processing
• Geoffrey Chan: Speech and signal processing, machine learning
• Joshua Marshall: Intelligent robotics
• Steven Blostein: Sensor networks, IoT, machine learning in wireless communications
• Jianbing Ni: Machine learning security and cybersecurity
• Il-Min Kim: Deep learning, reinforcement learning, IoT, mobile AI
• Ahmad Afsahi: High-performance deep learning
• Saeed Gazor: Machine learning, statistical image and signal processing
• Keyvan Hashtrudi-Zaad: Autonomous driving
• Karen Rudie: Discrete-event systems, intelligent agents
• Ning Lu: Internet of Things, communication networks for autonomous vehicles
• Shahram Yousefi: Machine learning in resource allocation, data storage, and telecom
• John Cartledge: Machine learning, optical communication
• Ryan Grant: AI/ML at Extreme-scale, AI/ML applications in Smart Networks

Vector Scholarships in Artificial Intelligence

To attract top students in Ontario and from around the globe into a growing number of AI-related master's programs, Vector's merit-based entrance scholarships recognize promising AI talent applying to Ontario universities. Scholarships are valued at $17,500 for one year of full-time master's study at an Ontario University.

Research

The Department of Electrical & Computer Engineering is home to nationally and internationally recognized researchers and cutting-edge research facilities. Our research is categorized into the areas of:

• Antennas
• Artificial Intelligence and Machine Learning
• Biomedical and Human-Machine Systems
• Communication and Signal Processing
• Engineering Education and Technology
• High Performance and Next Generation Computing
• Information and Software Security
• Networks and The Internet of Things
• Photonics, Nanotechnology & Integrated Circuits
• Power Electronics and Energy Systems
• Robotics, Autonomous Systems and Control
• Software Engineering

Career Opportunities

Our graduates have found careers:

• As university professors, including at the University of Toronto, University of British Columbia, Carleton University, and Institut national de la recherche scientifique (INRS)
• With high tech companies such as AMD, BlackBerry, Ciena, Cisco Systems, Google, Huawei, IBM, Intel, Infinera, Microsoft, Nokia
• With startup companies
• In service sectors such as financials, pension, actuarial, intellectual property

Program Details

The MASc program with a Field of Study in Artificial Intelligence is recognized by the Vector Institute for Artificial Intelligence as delivering a curriculum that equips its graduates with the skills and competencies sought by industry. The program prepares graduates through a combination of classroom and online learning, team-based problem-solving and course projects, research seminars, and faculty-supervised research projects. The student learning experience will be promoted through an inquiry-based curriculum.