Start dates
Starting in 2026, Fall (Sept)
Program length
18 months
Program Delivery
On-campus, Online, Hybrid* *based on program availability
Awards and Scholarships
More than 15 million in 2025
Shape the future of technology
Artificial intelligence is transforming the world. With a Master of Computer Science in Applied Artificial Intelligence (MCSAAI), you’ll be ready to innovate, solve complex problems, and lead the way forward.
Career highlights
With an MCSAAI, you will be well positioned for a growing number of roles in Canada’s evolving job market. These careers are in high demand across various industries.
Technology
Healthcare
Finance
Manufacturing
Talk to a Student Advisor
Course highlights
Term one courses
Machine Learning
This course covers key machine learning methodologies, including supervised (decision trees, neural networks, SVM), unsupervised, and reinforcement learning. It explores challenges, computational learning theory, and algorithm evaluation. Prerequisites include linear algebra, calculus, probability/statistics, and ideally, basic AI concepts.
Advanced Databases
A focus on algorithms and data structures crucial for modern database systems. It covers key aspects like buffer management, indexing, concurrency control, query optimization, and transaction management. The curriculum also explores database architectures, data models, and distributed database concepts, emphasizing security, integrity, and efficient data management techniques.
Artificial Neural Networks and Deep Learning
A look at fundamental and advanced neural network concepts, including deep learning principles, various network architectures (e.g., convolutional, recurrent), and optimization techniques (e.g., gradient descent). It explores applications in computer vision and natural language processing, focusing on statistical learning, loss functions, and practical implementations.
Term two courses
Computational Linguistics and Natural Language Processing
An introduction to the fundamentals of natural language processing (NLP), covering syntax, semantics, and pragmatics. Students will learn to develop NLP applications for tasks such as question-answering, sentiment analysis, translation, summarization, and chatbot creation. The focus is on enabling computers to understand and generate human-like language.
Foundations of Large Language Models
A primer on modern language modeling techniques and their practical applications, with a focus on transformer architecture and attention mechanisms. Initially, it delves into the probabilistic underpinnings of language models from a formal, theoretical angle and progresses to construction, training, and fine tuning of large-scale neural network models. Additionally, it covers systems programming, privacy concerns and societal impacts of AI including bias and misinformation.
Elective Course One
Choose one course from a list of electives, based on availability.
Term three courses
Image Processing and Pattern Recognition
This course empowers students to grasp the fundamentals of image processing and pattern recognition, enabling them to create software for automated analysis and interpretation of images and videos. It covers a comprehensive exploration of image processing techniques and theories, including spatial filtering, morphological processes, segmentation, and object recognition.
Advanced Topics in Artificial Intelligence
Exploring the forefront of artificial intelligence (AI), students will examine cutting-edge topics, methodologies, and applications shaping the field. Students will focus their attention on AI advancements in their chosen domain in preparation for their internship experience and capstone project.
Elective Course 2
Choose one course from a list of electives, based on availability.
Term five courses
Ethical Considerations with AI
Explore the ethical, social, and cultural implications of artificial intelligence (AI). This course examines the challenges AI presents to individuals, organizations, and society, focusing on issues like bias, fairness, privacy, and the impact on employment. Students will analyze real-world case studies and consider ethical frameworks for responsible AI development and deployment.
Internship
The Applied Artificial Intelligence Internship combines structured learning and experiential learning and provides the student the opportunity to apply the knowledge acquired during the program to a real-world setting.
Term six course
Capstone Project
Students complete a major AI consulting project with a client, focusing on project initiation, planning, execution, monitoring, controlling, and closing, guided by a faculty advisor.
These course highlights provide a glimpse into the Master of Computer Science in Applied Artificial Intelligence, your actual schedule may vary. There is a program break during Term 4. For full course descriptions and schedules, consult the Academic Calendar.
Career outlooks
Canada has been experiencing significant growth in the demand for AI professionals, reflecting the country’s commitment to technological advancement and innovation. From 2018 to 2023, there was a 37% increase in need for core AI skills, particularly in areas such as machine learning, deep learning, and AI ethics and governance.
The AI market in Canada Is projected to grow by 27.64% between 2025 and 2030, reaching an estimated market volume of US$18.50 billion by 2030.
Career path and salary
- Software engineer (AI focus) - $110,219
- AI specialist - $113,000
- Data scientist - $103,000
- AI engineer - $127,954
- Machine learning engineer - $118,378
*Source, Talent.com, Payscale, Indeed
Hear from our President and Vice-Chancellor
Designed for students with a background in mathematics and computer science, this program offers advanced training in machine learning, neural networks, large language models, data analytics, and AI ethics.
Admission requirements for the Master of Computer Science in Applied Artificial Intelligence program
Academic information
Applicants must meet the following minimum conditions for admission:
- Bachelor’s degree – Completion of a recognized undergraduate degree in computer science equivalent to the four-year honours degree standard, or relevant bridging studies, with CGPA of 3.0 (on 4.33 scale) or better.
- You must have successfully completed an undergraduate course in calculus.
- Students with a background in mathematics and computer science who do not hold an undergraduate degree in computer science will be considered for admission to the MCS Bridge Program.
Document checklist
Applicants must submit:
- A completed application form
- Official transcripts from all post- secondary institutions attended
- Official documentation confirming professional designations, where applicable
- Proof of English language proficiency, if applicable
International information
Applicants who completed undergraduate studies outside Canada must also submit:
- Certified translations of any documents not in English
- Documentation confirming award of their previous degree(s), if not already indicated on official transcripts
- A credential evaluation from a recognized service, if required by the registrar
Tuition information
Choosing to pursue a university education is a big commitment that impacts every aspect of your life – including your finances. Our fees are determined by the total cost of individual credits per academic year. All fees are listed in Canadian dollars and these rates are subject to change.
Awards and scholarships
The Office of the Registrar had dedicated more than $15 million in scholarships, awards and financial support to students in 2025. Entrance Awards are for newly admitted international and domestic students, while Academic Scholarships are for those entering the second term of their program.
Financial aid options
UNF has partnered with organizations to help newly admitted domestic students finance their education.
$22,500
Domestic tuition
$45,000
International tuition
$15 Million
Scholarship & awards
Frequently asked questions
What is the focus of the program's curriculum?
The program focuses on providing a strong foundation in machine learning, data analytics, and the ethical implications of AI. It emphasizes practical application through internships, a capstone project, and a focus on real-world problem-solving.
What are the program learning outcomes?
Key outcomes include collaboration and communication, leadership, systems thinking and complexity, ethics, global perspectives, digital mindset, knowledge and application.
What are the career prospects for graduates of this program?
Graduates can pursue careers in Artificial Intelligence, Machine Learning, Deep Learning, Applied Research, Data Analytics, and related fields.
Does the program address the ethical implications of AI?
Yes, the program includes a dedicated course on "Ethical Considerations with AI" and emphasizes the importance of ethical decision-making throughout the curriculum.
What kind of work-integrated learning experiences are included?
The program includes an internship where students gain real-world experience and a capstone project where they work with an external client to apply their AI skills.
Why choose UNF?
UNF is committed to innovative education and research for a digital world. This technology-centred approach puts you, the student, first. Learn from industry leaders and experienced faculty, gain experience through work-integrated learning components, and build a foundation that sets you on the path for success.
Contact your Student Advisor
Schedule an appointment with your dedicated Student Advisor at a time that’s convenient for you.
This institution has been granted a consent by the Minister of Colleges and Universities to offer this program for a five-year term starting June 12, 2025. Prospective students are responsible for satisfying themselves that the program and the degree will be appropriate to their needs (e.g., acceptable to potential employers, professional licensing bodies or other educational institutions.)
