This introductory module welcomes learners to the Microsoft AI Engineer Program, setting the stage for their journey toward becoming AI experts through a structured curriculum delivered in partnership with Microsoft and Simplilearn.

This optional foundational module introduces digital logic, data representation, programming essentials, compilers, interpreters, variables, loops, conditions, and writing programs using conditional statements, providing a beginner-friendly entry point into programming concepts.

This module equips learners with Python programming skills essential for AI development, covering the foundational programming concepts and tools needed to build and work with AI and machine learning models.

This module covers applied data science techniques using Python, enabling learners to work with real-world datasets, perform exploratory data analysis, and apply statistical and analytical methods to extract meaningful insights.

This module provides comprehensive training in machine learning concepts and algorithms using Python, enabling learners to build predictive models, perform feature engineering, and apply ML techniques to solve real-world problems.

This module provides comprehensive training in machine learning concepts and algorithms using Python, enabling learners to build predictive models, perform feature engineering, and apply ML techniques to solve real-world problems.

This module prepares learners for the Microsoft Azure AI-900 certification exam, covering Azure AI services, cloud-based AI tools, and fundamental concepts of artificial intelligence and machine learning on the Microsoft Azure platform.

This module covers building AI agents and extending Microsoft 365 Copilot using connectors, Copilot Studio, Azure AI Foundry, and SDKs, comparing low-code and pro-code development paths to create custom agents for real business use cases.

This module covers building AI agents and extending Microsoft 365 Copilot using connectors, Copilot Studio, Azure AI Foundry, and SDKs, comparing low-code and pro-code development paths to create custom agents for real business use cases.

The capstone project synthesises all skills and knowledge acquired throughout the program, requiring learners to apply AI and machine learning techniques to solve industry-specific challenges, demonstrating expertise in real-world scenarios and building a portfolio piece for potential employers.

This elective module provides an in-depth understanding of natural language processing and its applications in analysing vast amounts of language data, covering NLP techniques and tools used to build language-aware AI systems.

This elective module delivers advanced training in generative AI technologies, exploring cutting-edge techniques in large language models, AI-driven content generation, and advanced applications using tools such as Azure OpenAI, ChatGPT, and DALL-E.

This elective masterclass, delivered by industry experts, covers building and deploying agentic AI solutions using low-code tools like Copilot Studio and open-source frameworks such as AutoGen, enabling learners to rapidly implement agentic AI in real-world business environments.