Module 1: Foundations of LLM Models & Prompt Engineering

Overview

Generative AI is changing how businesses create content, analyse information, communicate and complete everyday tasks. Understanding how Large Language Models (LLMs) work and how to communicate with them effectively is an important first step in using AI at work.

In this module, you will get familiar with the Microsoft 365 Copilot interface, learn the fundamentals of prompt engineering and practise writing prompts for different business requirements.

You will also explore how Copilot Chat differs from Copilot app capabilities, understand knowledge graphs and vector stores, and compare leading LLM platforms such as ChatGPT, Claude, Gemini and Meta Llama.

The module builds a foundation for using AI tools more effectively, choosing the right tool for a task and getting useful results from AI in everyday business situations.

Tools covered: Microsoft 365 Copilot, Claude, ChatGPT, KIMI, Meta Llama and Google Gemini.

What Will Be Covered

1.1 Copilot Microsoft 365 Interface Walkthrough

Get familiar with the Microsoft 365 Copilot interface and understand how to access its main features.

You will learn about:

• Navigating the Copilot interface and understanding its main sections.

• Starting and managing conversations with Copilot.

• Entering prompts and reviewing AI-generated responses.

• Understanding how Copilot supports different Microsoft 365 applications.

• Identifying where Copilot can assist with everyday business tasks.

1.2 Basics of Prompt Engineering

Understand how prompts influence the responses generated by AI models and why clear instructions matter.

You will learn about:

• What prompt engineering is and how it works.

• The importance of context, instructions and expected output.

• Writing clear and specific prompts.

• Providing relevant information to improve response quality.

• Common prompting mistakes and how to avoid them.

1.3 Getting Started with Copilot Prompts

Learn how to interact with Copilot using practical prompts for common workplace requirements.

You will learn how to:

• Ask Copilot to explain topics and summarise information.

• Draft emails, reports and business documents.

• Extract key information from lengthy content.

• Rewrite and improve existing content.

• Generate ideas and organise information.

• Refine prompts when the initial response does not meet your requirements.

1.4 Prompting Techniques for Business Practitioners

Explore prompting techniques that help business professionals use AI for practical tasks across different departments.

You will learn how to:

• Give Copilot a clear role and business context.

• Define the task, expected output and format.

• Use examples to guide AI-generated responses.

• Break complex business requirements into smaller instructions.

• Build prompts for marketing, sales, HR, finance and operations.

• Review and refine responses to make them suitable for business use.

1.5 Copilot Chat vs App Skills

Understand the difference between using Copilot Chat for general AI assistance and using Copilot capabilities within individual applications.

You will explore:

• General conversations and information requests through Copilot Chat.

• Application-specific assistance in Microsoft 365.

• How Copilot supports tasks in Word, Excel, PowerPoint, Outlook and Teams.

• Choosing between Chat and application-based capabilities.

• Using the appropriate Copilot experience based on the task.

1.6 Knowledge Graphs vs Vector Stores

Understand two approaches used to organise and retrieve information for AI-powered applications.

You will learn about:

• What knowledge graphs are and how they represent relationships between information.

• What vector stores are and how they support similarity-based information retrieval.

• The difference between structured relationships and semantic similarity.

• How these approaches support information discovery and AI applications.

• Practical business examples of connecting and retrieving relevant information.

1.7 LLM Model Comparison – ChatGPT vs Claude vs Gemini vs Meta Llama

Explore leading Large Language Models and understand how their capabilities differ across common business tasks.

You will learn about:

• An introduction to ChatGPT, Claude, Google Gemini and Meta Llama.

• Comparing their capabilities, strengths and practical applications.

• Using different models for writing, research, analysis and problem-solving.

• Understanding differences in response quality, context handling and available features.

• Selecting an appropriate AI tool based on the task and business requirement.

Skills You Will Gain

By completing this module, you will develop the ability to:

• Navigate Microsoft 365 Copilot and use its key features.

• Write clear and effective prompts for different business requirements.

• Apply prompting techniques to generate more relevant and useful responses.

• Use AI tools for business writing, research, summarisation and information analysis.

• Understand the differences between Copilot Chat and application-based Copilot capabilities.

• Explain how knowledge graphs and vector stores support information retrieval.

• Compare different LLM platforms and identify suitable tools for different tasks.

• Recognise the importance of reviewing AI-generated content before using it in business activities.

Learning Outcomes

After completing this module, you will be able to apply generative AI to everyday workplace activities and make better use of AI tools across different business functions.

You will be able to:

• Reduce time spent on routine tasks: Use AI to prepare emails, summarise documents, organise information and draft business reports instead of starting every task from scratch.

• Improve communication across departments: Prepare clear business updates, meeting summaries, proposals and internal communications for different teams.

• Make better use of business information: Ask AI to extract key points, organise information and explain complex content in a format that is easier to understand.

• Improve the quality of business outputs: Provide the right context, instructions and examples to generate responses that better match your business requirements.

• Support cross-functional activities: Use AI to organise information from marketing, sales, finance, HR and IT for reporting, planning and coordination.

• Choose the right AI tool for the task: Understand the differences between leading AI models and select a suitable platform for writing, research, analysis and problem-solving.

• Improve workplace productivity: Use Copilot and other AI platforms to reduce repetitive work and spend more time on analysis, planning and decision-making.

• Use AI more responsibly: Recognise that AI-generated responses need to be checked for accuracy, relevance and suitability before being used in business decisions.

Microsoft AB-731 Exam Alignment

This module supports selected knowledge areas from the Microsoft Certified: AI Transformation Leader (AB-731) certification.

The AB-731 exam focuses on identifying the business value of generative AI, understanding Microsoft's AI applications and services, and identifying strategies for AI implementation and adoption.

Continue to the Next Module

You have completed the foundations of Large Language Models and prompt engineering.

You are now ready to explore how AI can be applied to everyday Microsoft 365 tasks and improve the way you work with documents, spreadsheets, presentations, emails and business communication.

Continue learning: Next Module 2: Microsoft Office Productivity Tools with Copilot

Explore how to use Copilot across Microsoft 365 applications to complete everyday workplace tasks more efficiently.