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.

Talk to an Advisor

Start Date

Open for enrollment

Start Date

Open for enrollment

Start Date

Open for enrollment

Program Duration

6 Months

Mon & Wed (18:00 - 21:00 hrs)

Program Duration

6 Months

Mon & Wed (18:00 - 21:00 hrs)

Program Duration

6 Months

Mon & Wed (18:00 - 21:00 hrs)

Learning Format

Intructor-Led (Live Project-Based Learning)

Individuals who want structure & accountability

Evenings, 2x per week (6-9 PM)

Live classes, group projects, custom labs, 1:1 support

Mentor-Guided (Self-Paced + Projects)

Motivated learners who want flexible learning with support

Flexible + weekly mentor
check-in

Guided labs, weekly mentor sessions, TA support, real projects

Self-Paced (Curated Path – Tech Pack)

Independent learners exploring a career path

Start Anytime

MCIT LMS curated path, one-time mentor onboarding, tools access

Intructor-Led (Live Project-Based Learning)

Individuals who want structure & accountability

Evenings, 2x per week (6-9 PM)

Live classes, group projects, custom labs, 1:1 support

Mentor-Guided (Self-Paced + Projects)

Motivated learners who want flexible learning with support

Flexible + weekly mentor check-in

Guided labs, weekly mentor sessions, TA support, real projects

Self-Paced (Curated Path – Tech Pack)

Independent learners exploring a career path

Start Anytime

MCIT LMS curated path, one-time mentor onboarding, tools access

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.

Course Outline

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

Applied Data Science with Python

ETL and Data Engineering

Microsoft Azure AI Fundamentals (AI-900)

AI Engineer Capstone Project

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

……………………..

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

……………………..

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

……………………..

SKILLS GAINED

……………………..

SKILLS GAINED

……………………..

SKILLS GAINED

……………………..

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

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

……………………..

Machine Learning using Python

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

……………………..

Microsoft Copilot Foundation

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

……………………..

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 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

……………………..

SKILLS GAINED

……………………..

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

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

……………………..

Applied Data Science with Python

Machine Learning using Python

ETL and Data Engineering

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

……………………..

Microsoft Azure AI Fundamentals (AI-900)

Microsoft Copilot Foundation

AI Engineer Capstone Project

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

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 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

……………………..

SKILLS GAINED

……………………..

SKILLS GAINED

……………………..

SKILLS GAINED

……………………..

Meet & Greet