About this Event
Duration:1 Full Day (8 Hours)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, Snacks and beverages will be provided during the session.
Course Overview
Montreal is recognized worldwide as a leading hub for artificial intelligence research and innovation, home to the Mila Institute and a thriving ecosystem of AI start-ups. Organizations across finance, gaming, aerospace, and tech are adopting AI and machine learning to stay competitive.
This 1-Day AI & Machine Learning Workshop equips professionals with the skills to understand core concepts, evaluate real-world applications, and leverage AI-driven tools for smarter decision-making. With Montreal’s rapid industry growth, these skills are essential for project managers and analysts aiming to drive innovation.
Learning Objectives
By the end of this training, you will be able to:
- Understand the fundamentals of AI and machine learning
- Recognize practical applications across industries (finance, gaming, aerospace, tech)
- Evaluate opportunities and limitations of AI in business projects
- Gain hands-on exposure to simple AI/ML models and tools
- Apply AI insights to project management and strategic decision-making
Target Audience
- Project managers in tech, gaming, finance, and aerospace
- Business analysts evaluating AI adoption
- Innovation and R&D professionals
- Professionals seeking to integrate AI into organizational strategy
Why It’s the Right Fit for You:
We align our training with the dynamic business environment of Montreal. As a global centre of AI excellence, the city demands professionals who can bridge technical understanding with business strategy. Our AI & Machine Learning workshop provides you with practical insights, industry-relevant case studies, and hands-on exercises to ensure skills can be applied immediately. Unlike theory-heavy programs, this training emphasizes actionable outcomes tailored to Montreal’s thriving innovation ecosystem.
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Smart Savings for Groups
Register in groups: 3 + participants save 10% each, while 10+ participants save 15% each.
Want this program tailored for your team?
Our In-House AI & Machine Learning Workshop adapts the curriculum to your company’s industry challenges—whether in finance, gaming, or aerospace. Delivered onsite or virtually, this approach fosters collaboration, reduces travel time, and allows you to work on real organizational data and use cases. In-house delivery creates a confidential learning environment where teams can explore AI opportunities directly relevant to their projects.
📧 Contact us today to schedule a customized in-house, face-to-face session:
Agenda
Welcome & Introduction
Info: • Workshop overview and participant introductions
• Montreal’s role in the global AI ecosystem
• Icebreaker: Participants share one way AI already impacts their daily work or industry.
Module 1: Introduction to AI & ML
Info: • Key concepts: supervised, unsupervised, deep learning
• Local case studies: Montreal’s AI start-ups & industries
• Case Study: Explore a Montreal-based AI start-up; discuss what made its AI adoption successful.
Module 2: Data Foundations for AI
Info: • Preparing quality data for machine learning
• Data pipelines and common challenges
• Activity: Identify potential data issues in a sample dataset (missing values, bias, duplicates).
Module 3: AI Applications in Business
Info: • Use-cases in finance, healthcare, gaming, and aerospace
• Evaluating ROI and risks of AI adoption
• Role Play: One team plays AI advocates pitching adoption; another plays executives questioning ROI and risks.
Module 4: Hands-On ML Basics
Info: • Simple predictive models with real-world datasets
• Using accessible tools (Python basics, AutoML platforms)
• Activity: Build a simple predictive model using a user-friendly AutoML tool; interpret the output.
Module 5: AI in Project Management
Info: • Integrating AI into workflows and decision-making
• Enhancing productivity and efficiency with AI tools
• Case Example: Review how project managers use AI scheduling and risk-prediction tools; group discussion.
Module 6: Ethics & Responsible AI
Info: • Addressing bias, fairness, and data privacy
• Canadian AI governance and ethical frameworks
• Case Study: Examine an example of AI bias in hiring; groups propose solutions for ethical use.
Module 7: Group Simulation – AI Use Case
Info: • Teams design an AI adoption plan for a case scenario
• Present recommendations and challenges
• Simulation: Teams act as consultants advising a Montreal company (finance, healthcare, or gaming) on adopting AI.
Module 8: AI Strategy & Future Trends
Info: • The future of AI in Montreal’s industries
• Preparing your organization for upcoming AI disruptions
• Activity: Individual reflection—write one step your organization should take in the next 12 months to prepare for AI.
Wrap-Up & Q&A
Info: • Group discussion
• Certificate distribution
• Closing Activity: Each participant shares one key insight and commitment from the day.
Event Venue & Nearby Stays
Regus Montreal, ON V6C 3E8 Canada, 1200 Avenue McGill College, Montreal, Canada
CAD 696.92 to CAD 910.92
