Master Certificate in Machine Learning Systems & Data Engineering | Montreal College of Information Technology

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Master Certificate in Machine Learning Systems & Data Engineering

Master Python, Applied Data Science, Machine Learning, ETL pipelines, and Azure AI—then build a real AI Engineering capstone project.
Learn hands-on from expert instructors with guided mentorship and job-focused training.
Build the skills to design, deploy, and manage production-level AI & Data Engineering systems. Become job-ready in 8 months.

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Master Certificate in Machine Learning Systems & Data Engineering

Duration

6 Months

Duration

6 Months

Duration

6 Months

Program Duration

10 months

Mon & Wed (18:00 - 20:00 hrs)

Start Date

Open for enrollment

Application closes on:

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Start Date

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Registration Deadline

Start Date

Talk to an Advisor

Registration Deadline

Start Date

Talk to an Advisor

Registration Deadline

Duration

6 Months

Duration

6 Months

Duration

6 Months

Learning Format

OnlineInstructor-LedOr Live Mentorshipfrom industry professionals

Program Overview

The Master Certificate in Machine Learning Systems & Data Engineering is an 8-month, instructor-led program that teaches you how to build practical, end-to-end AI solutions. You will learn Python, data science, machine learning, deep learning basics, and data engineering skills such as ETL pipelines and workflow automation.

The program also introduces Azure AI, Copilot, and cloud deployment tools so you can design and deliver AI systems in real environments. Through structured learning and hands-on projects, you’ll build the confidence to work on data-driven applications and support AI development in modern organizations.

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6 Months

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Tuition Fee

Duration

Start Date

Open for enrollment

Start Date

Oct 31, 2025

Duration

6 Months

Tuition Fee

Contact The Advisor

Enroll

Start Date

Oct 31, 2025

Duration

6 Months

Tuition Fee

Contact The Advisor

Enroll

Start Date

Oct 31, 2025

Duration

6 Months

Tuition Fee

Contact The Advisor

Enroll

Course Outline

Master Certificate in Microsoft AI Engineering program delivers an in-depth AI curriculum that includes Python fundamentals, data science, machine learning, deep learning, as well as specialized topics like NLP and Generative AI. Students gain practical experience through hands-on projects, real-world case studies, industry-relevant insights, and expert sessions led by Microsoft professionals.

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Python for AI

Develop strong Python programming skills as the foundation for your AI and ML journey. Learn to build intelligent systems, implement algorithms, and manage data efficiently using Python.

Concepts Learned:

Python syntax, constructs, and IDE setup
Data types, operators, loops, and conditionals
Python functions and modular programming
Object-Oriented Programming (OOP) in Python

SKILLS GAINED

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SKILLS GAINED

……………………..

Python for AI

Develop strong Python programming skills as the foundation for your AI and ML journey. Learn to build intelligent systems, implement algorithms, and manage data efficiently using Python.

Concepts Learned:

Python syntax, constructs, and IDE setup
Data types, operators, loops, and conditionals
Python functions and modular programming
Object-Oriented Programming (OOP) in Python

SKILLS GAINED

……………………..

Python for AI

Develop strong Python programming skills as the foundation for your AI and ML journey. Learn to build intelligent systems, implement algorithms, and manage data efficiently using Python.

Concepts Learned:

Python syntax, constructs, and IDE setup
Data types, operators, loops, and conditionals
Python functions and modular programming
Object-Oriented Programming (OOP) in Python

SKILLS GAINED

……………………..

Framer is a web builder for creative pros. Be sure to check out framer.com to learn more.

SKILLS GAINED

……………………..

Applied Data Science with Python

Master the end-to-end data science process, from data preparation to visualization. Gain practical expertise in Python libraries, hypothesis testing, and statistical modeling for business insights.

Concepts Learned:

Data science lifecycle and applications
Python for data science (NumPy, Pandas)
Linear algebra, statistics, and probability distributions
Hypothesis testing: Z-test, T-test, ANOVA
Data wrangling and preprocessing
Data visualization with Matplotlib, Seaborn, Plotly, and Bokeh

SKILLS GAINED

……………………..

Applied Data Science with Python

Master the end-to-end data science process, from data preparation to visualization. Gain practical expertise in Python libraries, hypothesis testing, and statistical modeling for business insights.

Concepts Learned:

Data science lifecycle and applications
Python for data science (NumPy, Pandas)
Linear algebra, statistics, and probability distributions
Hypothesis testing: Z-test, T-test, ANOVA
Data wrangling and preprocessing
Data visualization with Matplotlib, Seaborn, Plotly, and Bokeh

SKILLS GAINED

……………………..

Framer is a web builder for creative pros. Be sure to check out framer.com to learn more.

SKILLS GAINED

……………………..

Machine Learning using Python

Gain hands-on experience with supervised, unsupervised, and ensemble learning. Learn to build models, optimize pipelines, and implement ML solutions with TensorFlow, Keras, and PyTorch.

Concepts Learned:

Machine Learning fundamentals and pipeline
Supervised learning – regression and classification
Unsupervised learning – clustering and dimensionality reduction
Ensemble methods – bagging, boosting, stacking
Overfitting, underfitting, and performance evaluation

SKILLS GAINED

……………………..

Machine Learning using Python

Gain hands-on experience with supervised, unsupervised, and ensemble learning. Learn to build models, optimize pipelines, and implement ML solutions with TensorFlow, Keras, and PyTorch.

Concepts Learned:

Machine Learning fundamentals and pipeline
Supervised learning – regression and classification
Unsupervised learning – clustering and dimensionality reduction
Ensemble methods – bagging, boosting, stacking
Overfitting, underfitting, and performance evaluation

SKILLS GAINED

……………………..

Machine Learning using Python

Gain hands-on experience with supervised, unsupervised, and ensemble learning. Learn to build models, optimize pipelines, and implement ML solutions with TensorFlow, Keras, and PyTorch.

Concepts Learned:

Machine Learning fundamentals and pipeline
Supervised learning – regression and classification
Unsupervised learning – clustering and dimensionality reduction
Ensemble methods – bagging, boosting, stacking
Overfitting, underfitting, and performance evaluation

SKILLS GAINED

……………………..

ETL and Data Engineering

This module covers the fundamentals of ETL (Extract, Transform, Load) processes and data engineering. Learners will explore how to collect, transform, and load data efficiently, building robust pipelines that support analytics and machine learning workflows. Hands-on exercises using Python will prepare students to design, implement, and deploy data pipelines in real-world environments.

Concepts Learnt:

Basics of ETL processes and pipeline design
Core data engineering workflows and best practices
Data formats, storage, and database operations (SQL & NoSQL)
Data cleansing, validation, and quality assurance
Python-based ETL tools and frameworks (e.g., pandas, Airflow)
Pipeline deployment and monitoring

SKILLS GAINED

……………………..

ETL and Data Engineering

Basics of ETL processes and pipeline design
Core data engineering workflows and best practices
Data formats, storage, and database operations (SQL & NoSQL)
Data cleansing, validation, and quality assurance
Python-based ETL tools and frameworks (e.g., pandas, Airflow)
Pipeline deployment and monitoring

SKILLS GAINED

……………………..

ETL and Data Engineering

Basics of ETL processes and pipeline design
Core data engineering workflows and best practices
Data formats, storage, and database operations (SQL & NoSQL)
Data cleansing, validation, and quality assurance
Python-based ETL tools and frameworks (e.g., pandas, Airflow)
Pipeline deployment and monitoring

SKILLS GAINED

……………………..

Microsoft Azure AI Fundamentals (AI-900)

Prepare for the Microsoft AI-900 certification by mastering Azure AI services. Learn cloud AI fundamentals, governance, and compliance while working with Microsoft’s cloud-based AI solutions.

Concepts Learned:

Azure cloud and AI service overview
AI workloads, tools, and resources in Azure
Managing costs, governance, and compliance
Security and regulatory frameworks in Azure

SKILLS GAINED

……………………..

Microsoft Azure AI Fundamentals (AI-900)

Prepare for the Microsoft AI-900 certification by mastering Azure AI services. Learn cloud AI fundamentals, governance, and compliance while working with Microsoft’s cloud-based AI solutions.

Concepts Learned:

Azure cloud and AI service overview
AI workloads, tools, and resources in Azure
Managing costs, governance, and compliance
Security and regulatory frameworks in Azure

SKILLS GAINED

……………………..

Microsoft Azure AI Fundamentals (AI-900)

Prepare for the Microsoft AI-900 certification by mastering Azure AI services. Learn cloud AI fundamentals, governance, and compliance while working with Microsoft’s cloud-based AI solutions.

Concepts Learned:

Azure cloud and AI service overview
AI workloads, tools, and resources in Azure
Managing costs, governance, and compliance
Security and regulatory frameworks in Azure

SKILLS GAINED

……………………..

Microsoft Copilot Foundation

Learn how to design and build copilots using Microsoft Copilot Studio. Explore RAG-based copilots, prompt flow design, and grounding strategies to enhance AI-powered business tools.

Concepts Learned:

Copilot Studio interface and features
Bot creation, publishing, and performance analytics
Retrieval-Augmented Generation (RAG) copilots
Prompt flow design and model grounding

SKILLS GAINED

……………………..

Microsoft Copilot Foundation

Learn how to design and build copilots using Microsoft Copilot Studio. Explore RAG-based copilots, prompt flow design, and grounding strategies to enhance AI-powered business tools.

Concepts Learned:

Copilot Studio interface and features
Bot creation, publishing, and performance analytics
Retrieval-Augmented Generation (RAG) copilots
Prompt flow design and model grounding

SKILLS GAINED

……………………..

Microsoft Copilot Foundation

Learn how to design and build copilots using Microsoft Copilot Studio. Explore RAG-based copilots, prompt flow design, and grounding strategies to enhance AI-powered business tools.

Concepts Learned:

Copilot Studio interface and features
Bot creation, publishing, and performance analytics
Retrieval-Augmented Generation (RAG) copilots
Prompt flow design and model grounding

SKILLS GAINED

……………………..

AI Engineer Capstone Project

Bring together your AI, ML, and deep learning skills in a real-world project. Solve industry problems, apply best practices, and showcase your portfolio to future employers.

Concepts Learned:

Industry-specific AI problem-solving
End-to-end design of AI/ML solutions
Capstone project development and presentation

SKILLS GAINED

……………………..

AI Engineer Capstone Project

Bring together your AI, ML, and deep learning skills in a real-world project. Solve industry problems, apply best practices, and showcase your portfolio to future employers.

Concepts Learned:

Industry-specific AI problem-solving
End-to-end design of AI/ML solutions
Capstone project development and presentation

SKILLS GAINED

……………………..

AI Engineer Capstone Project

Bring together your AI, ML, and deep learning skills in a real-world project. Solve industry problems, apply best practices, and showcase your portfolio to future employers.

Concepts Learned:

Industry-specific AI problem-solving
End-to-end design of AI/ML solutions
Capstone project development and presentation

SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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SKILLS GAINED

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Applied Data Science with Python

Machine Learning using Python

ETL and Data Engineering

Microsoft Azure AI Fundamentals (AI-900)

Microsoft Copilot Foundation

AI Engineer Capstone Project

How to Apply

Scholarships

Financial Aid

Admission
process

Eligibility

Admission Process

Step 1: Book an Appointment with an Advisor
Step 2: Prepare Your Documents

Diploma and transcripts (High School, CEGEP, College, or University)
Birth Certificate (in English or French)
Proof of Canadian status
French language proficiency proof
Current resume
Two government-issued photo IDs
Step 3: Pay Application Fees
$50 application + $150 registration.

Step 4: Submit Your Application Form

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Financial Aid

Scholarships

Admission process

Eligibility

Our financial partners offer loans and personalized support to local entrepreneurs and internationally trained professionals.
You can also apply with the government to get financial aid through the AFE loan program (Aide financière aux études/Student financial assistance).

➔ Attend an Info Session  

➔ Meet an Advisor  

➔ Submit Documents  

➔ Get Scholarship  

➔ Begin your Career

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Scholarships

Admission process

Eligibility

➔ Meet an Advisor  

➔ Submit Documents  

➔ Get Scholarship  

➔ Begin your Career

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Scholarships

Financial Aid

Scholarships

Admission process

Eligibility

➔ Meet an Advisor  

➔ Submit Documents  

➔ Get Scholarship  

➔ Begin your Career

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