Program Overview

Skilled Trades & Technical Fields — Canadian Standards

AI & Data Science Bridging Program

A 40-hour, self-paced online bridging program designed for internationally trained professionals to strengthen practical AI and data analytics skills aligned with Canadian workplace expectations, ethics, and privacy awareness.

Format

100% Online

self-paced

Duration

40 Hours

4 modules

Curriculum

4 Modules

16 lessons

Credential

Certificate

Completion

Program Overview

The AI & Data Science Bridging Program (Canadian Standards) is a specialized certificate program designed to help
internationally trained professionals strengthen practical, job-relevant skills commonly expected by Canadian employers—
including working with real datasets, building clear analysis workflows, and communicating results in a professional format.

Across four structured modules, learners progress from AI/data science fundamentals to hands-on data analysis and visualization,
applied machine learning, and a capstone project. The program also emphasizes ethical technology practices and privacy awareness
relevant to Canadian workplaces (e.g., responsible use of data and AI in professional settings).

Who This Program Is For

Internationally trained professionals in IT, engineering, analytics, or technical fields
Graduates with theory-heavy backgrounds who need practical, tool-based readiness
Career changers preparing for entry-level data/AI roles in Canada
Professionals building a portfolio and workplace-style project presentation
Learners seeking Canadian-aligned documentation, communication, and teamwork expectations

Practical Benefits

Build hands-on confidence with applied analytics and AI workflows
Strengthen professional documentation, reporting, and presentation quality
Develop ethical and privacy-aware thinking for workplace projects
Practice Canadian-style collaboration and Agile-oriented workflow basics
Create a capstone project suitable for a starter portfolio

What You Will Learn

Data & Analytics Skills

Data collection, cleaning, and exploratory analysis (EDA)
Professional visualization and insights communication
SQL fundamentals for querying and data extraction

Applied AI & Workplace Readiness

Core machine learning concepts (supervised/unsupervised + intro to deep learning)
Model evaluation and basic deployment thinking (practical level)
Ethics, privacy awareness, Responsible AI, and Canadian workplace communication

Program Structure

Foundations of AI & Data Science in Canada
Data Handling, Analysis & Visualization
Machine Learning & Applied AI
Capstone Project & Canadian Workplace Integration

Certification

Participants who successfully complete the program receive the AI & Data Science Bridging Certificate
issued by Richmond Hill College.

This certificate confirms continuing education and professional development and does not grant licensure, immigration points,
or government-recognized professional designation.

Career Pathways Supported

Data Analyst (entry-level / junior)
BI / Reporting Analyst (tools-based roles)
AI / ML Assistant or Technician (support roles)
AI Support Associate / Analytics Support roles

The program supports readiness; hiring requirements vary by employer and role.

Compliance & Regulatory Statement (Important)

This program is delivered as continuing education and professional development.
It does not provide a regulated professional license and does not replace a college/university degree.
It does not guarantee employment, salary outcomes, or certification/exam success.
Ethics and privacy topics are educational and do not constitute legal advice; learners remain responsible for workplace compliance requirements.
Participants are responsible for meeting any employer, provincial, or federal requirements applicable to their work.

Curriculum

4 Sections
16 Lessons
40 Hours

Expand all sectionsCollapse all sections

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.
5
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.
5
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.
5
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.
5

Instructor

Soheil Najafi Mehri

31 Students

19 Courses

Student:

0 Students

Lesson:

16 Lessons

Duration: 40 Hours

Quiz:

4 Quizzes

Level: All levels

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