Harnessing AI Power – Machine Learning Training in Montreal (1 Day)

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.

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.

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

• 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

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. 

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:

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.

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.

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).

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.

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.

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.

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.

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.

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.

Info: • Group discussion

• Certificate distribution

• Closing Activity: Each participant shares one key insight and commitment from the day.

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