Learning Objectives

• Understand Microsoft’s end-to-end ecosystem: M365, Azure, Power Platform, Copilot, Copilot Studio
• Understand basic AI concepts: machine learning, deep learning, generative AI
• Learn fundamentals of prompting using Microsoft Copilot (Consumer + Enterprise)

Topics Covered

• What is Microsoft Azure and how does it differ from M365?
• Azure AI services overview (Cognitive Services, Azure OpenAI, Responsible AI)
• What is AI and how is it used in enterprises?
• What is Copilot? Where does it live?
• Prompting basics: task-based prompts, context, persona, format control

Hands-On

• Write prompts for document drafting
• Summaries, analysis, email writing, research tasks
• Build structured templates for business use cases

Learning Objectives

• Apply structured prompting frameworks
• Understand Microsoft’s Responsible AI principles
• Learn how to use Copilot and Azure AI safely and in compliance with organizational policy

Topics Covered

• Prompt engineering frameworks:
  • RACE (Role, Action, Context, Examples)
  • TACO (Task, Action, Constraints, Output)
  • Chain-of-Thought prompting
  • Multi-step prompting
• Troubleshooting bad prompts (hallucinations, vague prompts, missing context)
• Azure Responsible AI Principles: fairness, transparency, privacy, inclusiveness, accountability

Hands-On

• Rewrite weak prompts into strong ones
• Build prompts for HR, BD, operations, marketing
• Use Copilot with governance and security in mind

Learning Objectives

• Understand automation fundamentals
• Build low-code workflows using Power Automate
• Trigger flows from email, SharePoint, Excel, Teams

Topics Covered

• Types of flows: Automated, Instant, Scheduled, Business Process
• Connectors overview: Outlook, Teams, Excel, SharePoint, Dataverse
• When to automate vs when to use Copilot

Hands-On

• Automate email → Excel logging
• Automate approvals (manager approvals)
• Build a Teams notification bot
• Extract information using Power Automate AI Actions (OCR, translation)

Skill for AI-900

• Understanding how AI capabilities integrate inside Power Platform.

Learning Objectives

• Learn all core Azure AI services tested in AI-900
• Understand the difference between Cognitive Services vs Azure OpenAI
• Grasp ML basics in Azure

Topics Covered

• AI service categories:
  • Vision (OCR, image analysis)
  • Language (text analytics, NER, sentiment)
  • Speech (STT, TTS, translation)
  • Decision (Personalizer)
  • Azure OpenAI models (GPT, embeddings, fine-tuning basics)
• Understanding ML lifecycle: data → training → evaluation → deployment
• What is a model endpoint?

Hands-On

• Use Azure AI Vision to extract text
• Use Text Analytics to detect sentiment
• Try Azure OpenAI playground (classification + summarization)

Learning Objectives

• Understand how to build copilots/agents
• Learn about grounding, data sources, orchestration
• Build functional agents inside Copilot Studio

Topics Covered

• Overview of Copilot Studio
• Creating copilots
• Configuring topics, triggers, actions
• Adding data sources (SharePoint, Dataverse, websites)
• Prompt flows vs conversation flows
• Using generative answers backed by enterprise data

Hands-On

• Build a basic Q&A bot
• Connect a SharePoint knowledge base
• Add actions using Power Automate
• Publish and test inside Teams

Skill for AI-900

• GenAI concepts, enterprise data grounding, LLM-based apps.

Learning Objectives

• Understand ML workflow inside Azure ML Studio
• Train, validate, evaluate basic ML models
• Learn classification, regression, clustering at a foundational level

Topics Covered

• What is Azure Machine Learning?
• Designer (drag-and-drop) vs Notebooks
• Supervised vs Unsupervised learning
• Regression, classification, clustering examples
• Model evaluation: accuracy, precision, recall

Hands-On

• Use a built-in dataset
• Train a classification model using Designer
• Evaluate outcomes
• Deploy a model endpoint from Azure ML

Learning Objectives

• Understand NLP and GenAI fundamentals
• Work with Azure OpenAI for text generation, summarization, embeddings
• Build a mini-project using Azure AI

Topics Covered

• NLP basics: tokenization, embeddings, text classification
• What are LLMs?
• Use cases in enterprises (emails, customer service, RAG-based chatbots)
• Prompting RAG-style copilots

Hands-On Mini Project

• Build a text summarizer for documents
• Create a sentiment dashboard using Text Analytics
• Create a Q&A chatbot using Azure OpenAI + data source

Learning Objectives

• Learn Vision AI fundamentals
• Implement OCR, object detection, image classification using Azure Vision
• Final exam preparation for AI-900

Topics Covered

• What is Computer Vision?
• Azure Vision Services: OCR, tagging, face detection ethics
• Real-world use cases: manufacturing, retail, healthcare

Hands-On

• Upload images into Vision Studio
• Extract text
• Detect objects
• Build a simple image classifier using Azure ML Designer