Software Engineering Technology - Artificial Intelligence (Fast-Track, Online) (Optional Co-op)

How To Apply

A new intelligence is reshaping our world, transforming how we work and live. According to the McKinsey Global Institute, generative AI alone could add the equivalent of $2.6–$4.4 trillion annually to the global economy, and it will be at the core of every next-generation application.

The Software Engineering Technology - Artificial Intelligence (Fast-Track, Online) program is your launchpad into this revolution. Built in direct collaboration with industry leaders, our program ensures you graduate with the most in-demand, state-of-the-art skills to not just use AI but to build it from the ground up.

Your journey: From Foundation to Specialization

Our rigorous, project-based curriculum is structured around four core pillars of AI engineering, ensuring you build a deep theoretical understanding alongside industry-aligned practical skills.

Foundational AI and Machine Learning
- Core Concepts: Master the underlying theory of machine learning algorithms — including supervised, unsupervised, self-supervised, transfer and reinforcement learning — and then implement them hands-on using industry-standard frameworks and libraries like Sklearn, TensorFlow and PyTorch.
- Production Pipelines (MLOps): Learn to design, deploy and maintain robust machine learning pipelines with tools like Airflow, TensorFlow TFX and SageMaker pipelines.
Data Engineering and Scalable Systems
- Big Data Analytics: Process and analyze tabular, graph and streaming data using Spark and the Hadoop ecosystem.
- Data Pipeline Design: Learn to build, maintain and orchestrate robust data pipelines, which are the critical foundation for any AI system.
- Data Storage and Management: Gain proficiency in the full stack of data persistence, from SQL (e.g., Oracle, MS-SQL Server) and NoSQL (e.g., MongoDB) databases for operational data to Vector Databases (e.g., Chroma DB) for managing embeddings and powering GenAI applications like semantic search and RAG.
- Cloud-Native AI Development: Architect scalable, secure AI systems on cloud platforms.
- API-Centric Solutions: Rapidly integrate pre-built AI capabilities by leveraging Cloud AI APIs (e.g., for vision, speech and language) within microservices and serverless architectures.
- Custom ML Lifecycle Management: Build, train, deploy and manage the complete lifecycle of custom models using managed cloud platforms like SageMaker and SageMaker pipelines.
Cutting-Edge AI Specializations
- Generative AI and LLMs: Build advanced applications with Large Language Models, RAG frameworks and AI agentic workflows using LangChain, LangGraph and CrewAI.
- Intelligent Robotics: Architect autonomous robots by synthesizing perception, navigation and movement using Behavior Trees and LLMs within the ROS 2 framework to execute complex tasks in dynamic simulated environments.
- Advanced NLP: Build sophisticated natural language systems, such as intelligent chatbots capable of complex dialogue, understanding and generation.
- Recommender Systems: Design and build the intelligent recommendation engines that power e-commerce and social media.
Professional Software Engineering
- AI Project Management and Engineering: Develop expertise in the end-to-end process of delivering AI projects, from initial requirements engineering and planning to execution using a mix of methodologies, including Agile methodologies and modern MLOps pipelines.
- Full-Stack AI Development: Integrate AI models into full-stack applications using the latest AI stacks and architecture design patterns.
- Programming and Tools: Become proficient in Python, PySpark, JavaScript, C#, Java and Kotlin, and leverage AI-enhanced programming with tools like GitHub Copilot.
- AI Ethics and Data Governance: Incorporate foundational AI ethics — including fairness, bias elimination, transparency and privacy protection — directly into the design of AI capabilities and features.
- Human-Centered Design: Build accessible and intuitive interfaces for AI-powered applications.

Capstone Project: Build an AI Solution

Your journey culminates in an industry-inspired Capstone Project. You will go beyond integration; you will build a core AI solution from scratch that automates complex processes, unlocks insights from big data and solves a genuine business challenge, creating a powerful portfolio piece.

What You’ll Be Ready to Do

Graduate ready to make an immediate impact in Canada’s fast-growing AI sector. You will have the skills to:

Build Core AI from Scratch: Develop and train custom models using fundamental algorithms and diverse datasets to create unique AI capabilities.
Architect Scalable and Secure AI Systems: Design and deploy robust, governed AI pipelines and microservices on cloud platforms, implementing access control, data security, and cost-management for real-world production workloads.
Implement Ethical AI Foundations: Weave responsibility into the fabric of your work by designing systems with fairness, accountability and transparency from the ground up.
Master the Data Lifecycle: Manage the complete flow of data, the essential fuel for all intelligent systems.

Graduate with a rigorous foundation in the core disciplines of modern AI, ready to lead the development of secure, high-performance systems that will define the next generation of technology.

Please note: To select the co-op option, qualified students transfer to the co-op version (program #3442) of this program in Semester 5. A fully online fast-track version of this program may be available to qualified college or university graduates with a background in software. Fast-track applicants gain direct admission into Semester 3 of this three-year program and receive their advanced diploma in four semesters (program #3472) or with co-op that includes four semesters plus two work terms (program #3452). This program is available in an on-campus version at Progress Campus (program #3402) or with co-op (program #3412). The fast-track programs are also available in an on-campus version (program #3422) or with co-op (program #3432).

Program Overview

Your journey: From Foundation to Specialization

Our rigorous, project-based curriculum is structured around four core pillars of AI engineering, ensuring you build a deep theoretical understanding alongside industry-aligned practical skills.

Foundational AI and Machine Learning
- Core Concepts: Master the underlying theory of machine learning algorithms — including supervised, unsupervised, self-supervised, transfer and reinforcement learning — and then implement them hands-on using industry-standard frameworks and libraries like Sklearn, TensorFlow and PyTorch.
- Production Pipelines (MLOps): Learn to design, deploy and maintain robust machine learning pipelines with tools like Airflow, TensorFlow TFX and SageMaker pipelines.
Data Engineering and Scalable Systems
- Big Data Analytics: Process and analyze tabular, graph and streaming data using Spark and the Hadoop ecosystem.
- Data Pipeline Design: Learn to build, maintain and orchestrate robust data pipelines, which are the critical foundation for any AI system.
- Data Storage and Management: Gain proficiency in the full stack of data persistence, from SQL (e.g., Oracle, MS-SQL Server) and NoSQL (e.g., MongoDB) databases for operational data to Vector Databases (e.g., Chroma DB) for managing embeddings and powering GenAI applications like semantic search and RAG.
- Cloud-Native AI Development: Architect scalable, secure AI systems on cloud platforms.
- API-Centric Solutions: Rapidly integrate pre-built AI capabilities by leveraging Cloud AI APIs (e.g., for vision, speech and language) within microservices and serverless architectures.
- Custom ML Lifecycle Management: Build, train, deploy and manage the complete lifecycle of custom models using managed cloud platforms like SageMaker and SageMaker pipelines.
Cutting-Edge AI Specializations
- Generative AI and LLMs: Build advanced applications with Large Language Models, RAG frameworks and AI agentic workflows using LangChain, LangGraph and CrewAI.
- Intelligent Robotics: Architect autonomous robots by synthesizing perception, navigation and movement using Behavior Trees and LLMs within the ROS 2 framework to execute complex tasks in dynamic simulated environments.
- Advanced NLP: Build sophisticated natural language systems, such as intelligent chatbots capable of complex dialogue, understanding and generation.
- Recommender Systems: Design and build the intelligent recommendation engines that power e-commerce and social media.
Professional Software Engineering
- AI Project Management and Engineering: Develop expertise in the end-to-end process of delivering AI projects, from initial requirements engineering and planning to execution using a mix of methodologies, including Agile methodologies and modern MLOps pipelines.
- Full-Stack AI Development: Integrate AI models into full-stack applications using the latest AI stacks and architecture design patterns.
- Programming and Tools: Become proficient in Python, PySpark, JavaScript, C#, Java and Kotlin, and leverage AI-enhanced programming with tools like GitHub Copilot.
- AI Ethics and Data Governance: Incorporate foundational AI ethics — including fairness, bias elimination, transparency and privacy protection — directly into the design of AI capabilities and features.
- Human-Centered Design: Build accessible and intuitive interfaces for AI-powered applications.

Capstone Project: Build an AI Solution

What You’ll Be Ready to Do

Graduate ready to make an immediate impact in Canada’s fast-growing AI sector. You will have the skills to:

Build Core AI from Scratch: Develop and train custom models using fundamental algorithms and diverse datasets to create unique AI capabilities.
Architect Scalable and Secure AI Systems: Design and deploy robust, governed AI pipelines and microservices on cloud platforms, implementing access control, data security, and cost-management for real-world production workloads.
Implement Ethical AI Foundations: Weave responsibility into the fabric of your work by designing systems with fairness, accountability and transparency from the ground up.
Master the Data Lifecycle: Manage the complete flow of data, the essential fuel for all intelligent systems.

Graduate with a rigorous foundation in the core disciplines of modern AI, ready to lead the development of secure, high-performance systems that will define the next generation of technology.

Courses

Semester 1

Semester 2

Semester 3

Semester 4

Career Options and Education Pathways

Future Alumni

The graduates of Artificial Intelligence program can work on all software projects that involve intelligent use of data, such as machine learning, natural language processing, recommendation systems, image recognition, data analytics, big data, and more. The graduates can find employment in various financial, health, social and multimedia, insurance, telecommunications, large retail, tech start-up, transportation, and government companies and institutions.

Companies Offering Jobs

IBM Canada, Manulife, CIBC, RBC, BMO, Bell Canada, Scotiabank, TD, Toronto Transit Commission (TTC), American Express, Toronto Stock Exchange, Canadian Tire, Top Hat, SOTI, and more.

Program Highlights

Artificial Intelligence courses incorporate the use of leading technology geared to industry standards.
Project-based learning is a key component of the offering.
Knowledgeable and approachable faculty members have diverse industry experience and academic credentials.
Graduates from the program may apply for certified membership to their provincial engineering technology association.

Career Outlook

AI Developer
Software Engineer
Machine Learning Engineer
Data Analytics Developer
Software tester
Mobile application developer
Computer programmer
Systems analyst
Data analyst
Data Science Developer
Database Developer
Web application developer
Applications or software support

Education Pathways

Graduates of this advanced diploma program have the opportunity to apply learning achieved at Centennial for credits toward further study at the degree level.

For information on pathways and transfer credits, explore Centennial’s partner pathway options. Use the Education Pathways Checklist (pdf) as a guide as you explore your options.

For pathways to other Ontario post-secondary institutions, please visit ONTransfer.

Recognitions

OACETT

The Ontario Association of Certified Engineering Technicians and Technologists (OACETT) recognizes this TAC nationally-accredited program as meeting the academic standard for certification in the Certified Engineering Technologist (C.E.T.) category as well as the OACETT technology report and language benchmark requirements.

OACETT logo

Accreditation

CIPS

This program has met the national educational standards of Canada’s engineering technology and applied science profession, as such, has received national program accreditation by Canada's Association of Information Technology (IT) Professionals (CIPS).

CIPS Logo

TAC

National Accredited Program logo

Please note: The qualification requirements and costs for each external accreditation, designation, certification or recognition are set by the granting body — not by Centennial College. In order to qualify for any external accreditations, designations, certifications or recognition, students, and graduates will need to follow the processes and meet the applicable

Academic Pathways

Artificial Intelligence advanced diploma is open to graduates from Software Engineering Technology or similar programs, as well as to anyone with a degree in the computing field. The graduates of this program can pursue a university degree in all institutions available to our Software Engineering Technology graduates. This includes:

University of Guelph, Ontario
Trent University, Ontario
Ryerson University, Ontario
University of Ontario Institute of Technology, Ontario
Algoma University, Ontario
Laurentian University, Ontario

Admission Requirements

Academic Requirements

Degree or diploma in computer science, information technology, software engineering, or a related discipline

Additional Requirements

Co-op Option

The co-op option in this program will provide you with the opportunity to gain hands-on experience while you complete two co-op work term as an employee in the field. This experience not only allows you to put classroom learning into practice, but will also provide valuable contacts for your future career.

To participate in this co-op option, you will need to complete an application process in semester 1. If academically qualified, you may be admitted to the co-op program. Academically qualified students who are accepted into the program will register for the co-op preparation course as scheduled.

Co-op Requirements

Minimum of 80% of courses completed from semester one
Completion of COMM160/161 by the end of semester 1 with a C grade (60%) or higher
A cumulative GPA of 2.5 or higher (this must be maintained for the duration of the program)
Students must be legally eligible to work in Canada
Students who meet the above prerequisites will submit their application for co-op to the Career Services & Cooperative Education Department in semester 1

Note: Meeting the minimum co-op program requirements does not guarantee admission into the co-op program.

Co-op Model Route

Fall Semester Intake
Fall	Semester 1
Winter	Semester 2
Summer	Co-op Work Term 1
Fall	Semester 3
Winter	Co-op Work Term 2
Summer	Break
Fall	Semester 4

Learn more about co-op programs.

How to Apply

1. Apply Online

Domestic Students

If you are applying through the Better Jobs Ontario Program, please work with an Employment Ontario service provider. For more information go to Better Jobs Ontario Program.

If you have previously attended a full-time program at Centennial College, you may be eligible for a Program Transfer. Visit Enrolment Services at any Campus for information.

All other applicants must apply online at Ontariocolleges.ca. A non-refundable application fee must accompany applications. The fee is payable online, by telephone, online banking, by mail, or in-person to Ontariocolleges.ca. For more information go to Ontariocolleges.ca Application Fees.

International Students

Apply directly to Centennial College here.

2. Submit Documents

Domestic Applicants

Current Ontario high school students and graduates from Ontario high schools: Notify your guidance counsellor that you have applied to college and your school will forward transcripts to Centennial College via Ontariocolleges.ca.

Graduates of college/university, or high school outside Ontario but within Canada: You are responsible for requesting that your educational institute sends any required documents and transcripts to Ontariocolleges.ca.

International Applicants

Please refer to the International Education Application Guide.

3. Confirm Your Offer of Admission

Offers of Admission are sent by mail to eligible applicants. When you receive your offer, you must login to your account at Ontariocolleges.ca and confirm before the Deadline to Confirm noted in your offer letter.

You may confirm only one college and one program offer at a time.

You must confirm your offer by the Deadline to Confirm noted in your Offer of Admission letter or your seat may be given to another applicant.

When you confirm your Offer of Admission at Centennial College you are given access to your personal myCentennial account where you can check your email, grades, register for courses, pay tuition fees, and see your class timetable.

4. Pay Fees

Centennial fees statements are sent by email to your personal email account and to your myCentennial email account. Fees statements are not mailed.

You must make a minimum payment by the Fees Deadline noted in your Fees Statement or your seat may be given to another applicant.

5. Build Your Timetable (Register for Courses)

Build your timetable (web-register for courses) at my.centennialcollege.ca.

Your web-registration will not open if:

You have not submitted your minimum fee payment by the deadline
You received a Conditional Offer of Admission and you have not met the conditions of your offer.

Once you have paid your fees or have made appropriate arrangements, register for your courses online through myCentennial.

Tuition and Fees

Fees noted below are estimates only. Tuition is based on two semesters, beginning Fall 2025.

Student	Tuition (2 Semesters)	Ancillary Fees	Total
Canadian	$3,114.00	$619.92	$3,733.92
International	$18,254.00	$1,305.55	$19,559.55

Technology Requirements

Students in this program must have consistent access to a mobile computing device that meets or exceeds the recommended hardware requirements below.

Students with Accessibility Needs: If you require accommodations for a documented disability, please consider your adaptive technology needs when selecting a device for your program. To access disability services, you can make an appointment with the Centre for Accessible Learning and Counselling Services (CALCS) by calling 437-568-4799 or emailing calcs@centennialcollege.ca.

Students in this program will need to have consistent access to the following:

Laptop Requirements:
- 13-inch screen, full HD resolution
- 16 GB RAM
- 512 GB SSD
- high end graphics card, VR ready (Nvidia 1060 or better recommended)
- Intel Core i7 (6th generation or later) or equivalent; x64-based processor
- USB and HDMI ports
- Windows 11 OS
- audio/microphone combo
- webcam
Recommended:
- built-in ethernet port
- battery life of three (3) hours or more
- 15-inch touchscreen

Please note: Chromebooks are NOT acceptable alternatives. Some courses may require additional devices, such as an external hard drive.

Minimum Internet Requirement:

You will need regular access to a computer with an internet connection. High-speed broadband access (LAN, cable or DSL) with a minimum download speed of 50 Mbps is highly recommended.

ClassAPPs 2.0

Students are encouraged to use Centennial College’s ClassAPPs 2.0, an all-in-one system that provides access to the digital tools needed to complete college courses from home or any other location at any time. Any student can use ClassAPPs 2.0 with any modern HTML5-enabled web browser, such as Chrome, Edge or Firefox. Simply log in using the same ID and password used for College PCs to access cloud-based software and other learning resources.

Program Vocational Learning Outcomes

Program Vocational Learning Outcomes describe what graduates of the program have demonstrated they can do with the knowledge and skills they have achieved during their studies. The outcomes are closely tied to the needs of the workplace. Through assessment (e.g., assignments and tests), students verify their ability to reliably perform these outcomes before graduating.

Analyze and define the specifications of a software system based on requirements engineering processes and techniques.
Design, develop, integrate, document, implement, maintain and test secure software systems based on software engineering methodologies, modern programming paradigms and frameworks.
Analyze, evaluate and apply appropriate software engineering design techniques, data structures and algorithms, and patterns to the implementation of a software system.
Design and implement appropriate testing, verification and evaluation procedures to assess software quality and improve software performance.
Design, model, implement, optimize and maintain a database, data mining, or big data solutions.
Develop and maintain software systems through the application of networking concepts as related to distributed systems and AI implementations.
Analyze, design, and implement integrated AI solutions that address issues of data privacy and security.
Work effectively as a member of a software development team on the design, implementation and testing of a software system.
Use project management principles, tools and techniques to ensure the timely and successful completion of projects.
Analyze and design effective data visualizations to provide business insights to AI solutions and communicate information to the viewer.
Complete all work in compliance with laws, regulations, data governance, and professional ethics relevant to the AI industry.
Develop and implement strategies for personal, career and entrepreneurial development to enhance work performance and maintain currency with the AI industry.
Analyze, evaluate, and integrate machine learning algorithms into various applications to support decision-making and build automated software solutions.
Evaluate AI tools and techniques to design software solutions for a variety of business problems.
Design, develop, and deploy various intelligent conversational interfaces for different platforms.

Advising

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