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Yes—Seneca Polytechnic is now delivering a real, standalone master’s degree in artificial intelligence. Its Master of Artificial Intelligence Design & Development (MAI) began with a January 2026 cohort. The current catalog describes a full-time, four-semester (16-month) hybrid program at the Newnham Campus in Toronto, with 840 hours of work-integrated learning. That makes it an applied option for students who want production-oriented AI training, but it is not yet a proven employment shortcut or a substitute for every research-focused university master’s.
What Seneca is offering
The official credential is the Master of Artificial Intelligence Design & Development, abbreviated MAI. It is offered by Seneca Polytechnic’s School of Software Design & Data Science at the Newnham Campus in Toronto.
- Credential: master’s degree
- Study mode: full-time
- Delivery: hybrid, combining online and in-person learning
- Current duration: four semesters, or 16 months
- Listed start terms: January, May and September, subject to availability
Seneca announced the degree on September 12, 2025, with applications for a January 2026 start. On February 18, 2026, it said the first cohort was in session. Seneca calls it the institution’s first master’s degree and says it is the first master’s of its kind offered by an Ontario college or polytechnic. That “first of its kind” description is Seneca’s claim, not a broader claim that it is Ontario’s first AI master’s of any type.
Seneca’s launch announcement and first-cohort update provide the institutional timeline.
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Why the launch matters
Ontario’s graduate education market is dominated by universities, while colleges and polytechnics have traditionally emphasized applied diplomas and degrees. Seneca’s MAI tests whether a polytechnic can deliver graduate-level AI training around implementation, workplace projects and employability rather than a primarily academic research model.
The distinction matters when comparing credentials. A university thesis master’s may be designed around original research and doctoral preparation. Seneca’s published structure instead combines advanced technical courses, applied research projects and a substantial internship component. Neither model is automatically better; they serve different outcomes.
What students study
The course sequence covers the mathematical, technical, operational and organizational sides of AI.
First semester
- Machine Learning
- Mathematics for Machine Learning Algorithms
- Data Science for Artificial Intelligence
- Artificial Intelligence Project Management
- Ethics in Artificial Intelligence
Second semester
- MLOps
- Deep Learning
- Natural Language Processing
- Computer Vision
- Artificial Intelligence Research
Later semesters
- Applied Research Project
- Applied Research Project II
- Internship I
- Internship II
This mix is broader than a model-building curriculum alone. Machine learning, deep learning, NLP and computer vision address core methods; MLOps addresses deployment and maintenance; mathematics supports algorithmic understanding; project management and ethics address organizational and responsible-use concerns.
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The complete course list and delivery information are on Seneca’s MAI courses page.
How the 840-hour internship component works
Seneca advertises 840 hours of work-integrated learning in the final two semesters. Students may complete that requirement through either:
- two separate four-month internships; or
- one eight-month internship.
A placement can be in person, online or hybrid, depending on the hiring organization. The published material establishes a curricular work-integrated-learning requirement; it does not establish that every student receives a paid placement, that a placement is guaranteed, or that an internship leads to a job.
Applicants should therefore ask admissions staff how placements are sourced, what happens if a student cannot secure one, whether compensation is typical, and how the schedule interacts with the student’s existing work or immigration status.
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Hybrid does not mean fully online
Seneca says courses can be online, in person, hybrid, or delivered flexibly while an instructor teaches in a classroom and streams to remote students. The schedule identifies some subjects—such as mathematics, AI ethics and AI research—as explicitly in person, while other subjects may be hybrid or online. Preferred delivery options may be assigned on a first-come, first-served basis.
That distinction is especially important for international students. Seneca labels the program PGWP-eligible, but online study and required in-person attendance can affect Post-Graduation Work Permit eligibility under current federal rules. Students should confirm the applicable requirements with Immigration, Refugees and Citizenship Canada and follow the attendance pattern stated in their official documents. The program should not be treated as an entirely remote degree.
Current intakes and availability
The following was listed on Seneca’s program page on August 18, 2026. Availability can change, and an “open” listing does not guarantee admission or a seat.
| Applicant group | September 2026 | January 2027 | May 2027 |
|---|---|---|---|
| Canadian applicants | Waitlist | Open | Open |
| International applicants | Closed | Open | Open |
Check the live MAI program page before paying an application fee, arranging travel or resigning from employment.
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Admissions and preparation
Seneca’s admissions page should be treated as the controlling source for prerequisites and documents. The institution says equivalency may be considered using academic transcripts, a résumé and a letter of interest, with relevant professional experience taken into account. That is not an automatic pathway for applicants without computing preparation.
Applicants should be ready to demonstrate sufficient programming, quantitative and software-development background for machine learning and data-science coursework. Candidates from nontraditional backgrounds should request a written assessment from Seneca before committing relocation costs or tuition. See the current admission requirements for the complete criteria.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Tuition and the cost decision
These are Seneca’s approximate amounts viewed on August 18, 2026. Books and supplies are extra, and fees can change without notice. Tuition is divided into four payments due on the first day of each term.
| Applicant group | Approximate per semester | Approximate four-semester total |
|---|---|---|
| Canadian applicants | C$3,941 | C$15,764 |
| International applicants | C$10,000 | C$40,000 |
The totals exclude housing, transportation, food, health coverage, immigration expenses and other living or study costs. Seneca also advertises renewable scholarships of up to C$1,000 per year for eligible full-time degree students; eligibility and award amounts must be confirmed with the institution. Current figures are on the official costs page.
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Domestic students should separately check whether OSAP or other aid applies to this credential and intake. International students should build a budget around the full cost of living in Toronto, not tuition alone.
A timeline discrepancy applicants should understand
Seneca’s September 2025 launch release called the degree a two-year program. Its current program catalog lists four semesters, or 16 months. Use the current catalog and the duration stated in an offer document when planning costs, immigration paperwork and time away from work.
Who is the strongest fit?
Likely good fit
- Software developers, data engineers, analysts or technical professionals seeking a formal AI specialization.
- Computing graduates who want exposure to production systems, deployment and business use cases.
- Students who value internships and applied research more than a thesis-centered route.
- Candidates seeking a shorter listed program than many two-year graduate degrees.
Potentially weaker fit
- Applicants targeting a PhD or a heavily theoretical research career.
- Candidates without adequate mathematics, programming or software-development preparation.
- Professionals who need an entirely asynchronous online schedule.
- International students who have not verified study-permit, attendance and post-graduation work rules.
How to compare it with alternatives
Compare the purpose of each credential rather than prestige alone:
| Option | Usually best for | Questions to ask |
|---|---|---|
| Research-oriented university master’s | Thesis work, academic research and PhD preparation | Is there a thesis, supervisor and funded research pathway? |
| Course-based professional master’s | Advanced coursework and industry preparation | How do its capstone, internship, employer links and delivery compare? |
| Graduate certificate or postgraduate diploma | Lower time and financial commitment or prerequisite building | Is the credential sufficient for the intended role, and is it actually equivalent to a master’s? |
| Boot camp, vendor certification or online course | Fast, flexible technical upskilling | Will the learner gain the depth, credential and supervised experience needed? |
The key question is what you are buying: a recognized graduate credential, a research pathway, an internship-heavy applied experience or faster technical skills.
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Because the first cohort only began in 2026, there is not yet a graduating-class record for this specific degree. Public program information does not establish:
- graduate employment or salary outcomes;
- the percentage of students placed in internships;
- typical internship pay;
- a complete employer roster or placement-quality measure;
- results from the first graduating cohort;
- a long-term academic reputation; or
- how graduates progress into doctoral study.
Seneca’s descriptions of career possibilities are possibilities, not measured placement guarantees. Ask for current outcome and placement data before treating the degree as an investment with a predictable financial return.
The Bottom Line
Bottom line: Seneca’s MAI is a genuine new master’s degree with a 16-month catalog listing, applied AI coursework and an unusually large 840-hour work-integrated-learning component. It merits consideration from students seeking practical AI deployment experience, but applicants should verify the live intake, full budget, in-person schedule, admissions fit and international rules—and weigh its unproven graduate outcomes against the goals of a research university degree.
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