AI & Data Science Bridging Program – Canadian Standards

The AI & Data Science Bridging Program at Richmond Hill College is a specialized online certificate designed for internationally trained professionals who want to upgrade their AI, data science, and analytical skills to meet Canadian industry standards.

In many countries, academic programs focus heavily on theory, while Canadian employers expect practical, hands-on experience with tools, real datasets, workplace communication, and a strong understanding of ethics and privacy regulations. This bridging program closes that gap by offering a structured learning pathway across four modules, covering AI foundations, data analytics, machine learning, and real-world project development.

Learners gain practical experience with tools such as Python, Pandas, Matplotlib, SQL, Power BI, and machine learning frameworks. They also learn essential Canadian workplace competencies including documentation, communication, teamwork, Agile workflow, and ethical technology practices (PIPEDA, PHIPA, Responsible AI).

Upon successful completion, students earn the AI & Data Science Bridging Certificate – Richmond Hill College, demonstrating readiness for entry-level and intermediate roles such as Data Analyst, AI Assistant, Machine Learning Technician, BI Analyst, and AI Support Associate in Canada’s rapidly growing technology sector.

Curriculum

4 Sections
16 Lessons
40 Hours

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Module 1: Foundations of AI & Data Science in Canada
This module introduces learners to the core concepts of Artificial Intelligence, Machine Learning, and Data Science, with a focus on how these technologies are applied in Canadian industries. Students explore the full data science lifecycle, essential tools, and workplace expectations in Canada’s tech environment. Emphasis is placed on professional communication, documentation standards, and understanding how interdisciplinary teams collaborate within Canadian organizations.
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Module 2: Data Handling, Analysis & Visualization
This module provides hands-on training in managing, analyzing, and visualizing data—key skills required for data-related jobs in Canada. Students work with real datasets to practice data cleaning, preprocessing, exploratory data analysis (EDA), and creating clear, professional visualizations used in Canadian business settings. SQL fundamentals for data science are also introduced to build essential querying and database skills.
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Module 3: Machine Learning & Applied AI
This module builds foundational machine learning skills through supervised, unsupervised, and introductory deep learning techniques. Students learn how to design ML models, implement algorithms using Python, evaluate performance, and understand practical deployment considerations. The module emphasizes applying AI ethically and efficiently within Canadian workplaces.
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Module 4: Capstone Project & Canadian Workplace Integration
In this final module, learners complete a real-world capstone project using the full AI and data science workflow. Students apply Agile project planning, develop an AI/analytics solution, and prepare a final presentation aligned with Canadian workplace expectations. The module also focuses on ethics, privacy compliance, Responsible AI principles in Canada, and job readiness, including portfolio development and resume alignment.
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