AI and Machine Learning are transforming industries—from healthcare and finance to transportation and entertainment. With increasing demand for intelligent automation and data analysis, skilled professionals in AI & ML are highly sought after across Canada and globally.
The program blends theory with practical sessions, allowing students to work with real datasets, machine learning models, and neural networks. You’ll gain experience using Python, TensorFlow, and other industry-standard tools to build, train, and evaluate intelligent systems.
Graduates can pursue roles such as Data Analyst, Machine Learning Engineer, AI Developer, or Research Assistant. The program also lays the groundwork for further specialization in deep learning, natural language processing, and AI ethics.
We deliver industry-aligned trades training that prepares students to enter the workforce with confidence.
“To empower learners with practical skills and Red Seal–aligned training for successful careers in the trades.”
“To be Ontario’s most trusted source for career-focused technical education.”
Our Mississauga campus is located in the central GTA, easily accessible by major highways and public transit.
The Artificial Intelligence & Machine learning course at Futures introduces students to the core concepts of artificial intelligence and machine learning, including supervised and unsupervised learning, neural networks, model evaluation, and reinforcement learning. Students will explore real-world applications and develop the ability to design, train, and optimize intelligent systems.
Students engage in hands-on exercises using real datasets, machine learning libraries (e.g., scikit-learn, TensorFlow), and coding environments to simulate real-world AI development workflows. Projects include building predictive models, training neural networks, and optimizing algorithms for performance.
The course content reflects current trends and employer expectations in AI and data science. Topics like deep learning, model evaluation, and reinforcement learning are aligned with the skills demanded by tech companies and research institutions.
Throughout the program, students build a portfolio of completed projects, including supervised and unsupervised learning models, neural network architectures, and reinforcement learning simulations. This portfolio serves as a showcase for job applications and interviews.
Students receive resume-building assistance, interview coaching, and job search guidance tailored to AI and tech roles. The program also includes certification of readiness support and access to job postings through our alumni network.
39.5 Level 1: Introduction to Automotive Service
39.5 Level 2: Chassis and Drivetrain Systems
39.5 Level 3: Engine and Electrical Diagnostics
39.5 Level 4: Advanced Diagnostics and Shop Practice
Workshop safety and tools; vehicle systems & engine fundamentals; tires, wheels, and basic servicing; preventive maintenance and inspection
Suspension and steering systems; brake and drivetrain systems; cooling and lubrication systems; exhaust and fuel systems
Engine performance and management systems; electrical and electronics systems; heating, ventilation & air conditioning (HVAC); hybrid and electric vehicle technology
Advanced diagnostics and driveability; onboard computer systems & troubleshooting; shop and business management; certification and customer relations
Introduction to AI & ML
Neural Networks & Deep Learning
Supervised Learning
Unsupervised Learning
Deep Learning & Neural Networks
Model Evaluation & Optimization
Reinforcement Learning
Overview of Artificial Intelligence and Machine Learning, historical context and future trends applications across industries
Structure and function of neural networks, introduction to deep learning architectures, use cases and implementation
Regression and classification technique, model training and evaluation, real-world applications
Clustering and dimensionality reduction, pattern recognition and anomaly detection
Advanced neural network models, convolutional and recurrent neural networks, training strategies and optimization
Performance metrics and validation techniques, hyperparameter tuning and cross-validation, bias, variance and overfitting
Core concepts and algorithms, exploration vs. exploitation, applications in robotics and gaming
Submit required academic and ID documentation
Pick your schedule from available class schedules.
Contact our Registrar at (905) 412‑3007 or email info@futurescollege.ca
Attend, train, and get Futures ready!
Online or in-person
(if specifically asked for)
A: No, the program is beginner-friendly but familiarity with basic coding helps.
A: Yes, graduates can apply for entry-level roles or internships in AI/ML.
A: Yes, it aligns with industry expectations and technical standards.
A: Recorded sessions and guided reviews are available.
A: Yes, flexible payment plans and funding options are available. Contact Admissions for details.
Students can explore available funding options through our Student Resources page or contact our Admissions Team for personalized assistance with financial planning and payment options.
Tuition: CAD $ 1995 (includes lab materials, certification prep, logbook)
Optional Extras:
Price with Discount/ Scholarship- 1495 CAD $ (Terms and Conditions Apply)
Eligible students may benefit from:
Enrollment Tip:Contact our Financial Office early—let us assist you with grants, loans, and sponsorships. Rates (or prices) may vary based on time and conditions.
Futures Canadian College of Business, Health and Technology's mission is to inspire our students from all communities
