# Microsoft Copilot LMS Chapters

The Microsoft Copilot LMS provides a structured learning experience covering
prompt engineering, Microsoft 365 productivity, business analytics, workflow
automation, and AI agent development. Each section includes resources and
practical activities designed to help learners build their skills and apply AI
to everyday tasks and business challenges.



Getting Started





The Getting Started section helps learners prepare for the program and stay
informed throughout their training. Access the program brochure, demo class
recordings, live demo sessions, academic calendar, upcoming schedules, enrolment
information, and student study kit. These resources make it easier to understand
the program structure, prepare for classes, and keep track of important learning
activities.



Prompt Engineering





Learn how to communicate with AI more effectively by writing clear, structured,
and context-aware prompts. This section covers prompting formulas, persona-based
prompting, descriptive and instructional prompts, creative prompting, and
techniques for business users. The MS Office prompt library and collection of
300 personas provide practical examples that learners can adapt to different
roles and tasks, helping them generate more relevant responses and improve the
quality of AI-assisted work.



Module 1: Foundations of LLM Models & Prompt Engineering



Build a strong foundation in large language models and Microsoft 365 Copilot
before moving into advanced applications. Learners explore the Copilot
interface, prompt engineering basics, and techniques for writing effective
business prompts. By the end of this module, they should be able to navigate
Copilot confidently and use well-structured prompts to support everyday
productivity and professional tasks.



Module 2: Microsoft Office Productivity Tools with Copilot



Discover practical ways to use Copilot across Excel, Outlook, Word, and Teams.
Learn to work with formulas, functions, pivot tables, charts, and dashboards in
Excel; draft and respond to emails in Outlook; refine documents and summarise
information in Word; and extract insights from meeting notes and transcripts in
Teams. The focus is on reducing repetitive work, handling information more
efficiently, and producing clearer, more useful business outputs.



Module 3: Persona-Based Prompting, Projects & Notebooks



Explore how AI responses can be tailored to specific professional roles,
responsibilities, and business requirements. This module covers role-specific
prompting for analysts, managers, and strategists, along with customised
notebooks and project-based context. Learners develop a better understanding of
how to organise information and create focused AI-assisted workflows that suit
their individual tasks and working methods.



Module 4: Research, Analytics, KPIs & Strategy with AI Agents





Use AI-assisted analytics to explore business information and identify insights
that support decision-making. Learners examine how analytics agents can work
with Excel sheets, PDFs, CRM feeds, Microsoft Fabric, Azure data sources, and
other enterprise resources. The objective is to move beyond reviewing raw
information and develop the ability to identify patterns, assess KPIs, and use
data to support business planning and strategy.



Module 5: Workflow Automation, Enterprise AI Tools & Business App Creation Using
AI





Learn how AI tools can support business application development and automate
repetitive processes. This module explores app creation using Power Apps and
Copilot, workflow automation with Power Automate, and connections between
applications and enterprise data. Learners also work through use cases involving
OneDrive document management, SharePoint content creation, and connected
business workflows, building an understanding of how automation can reduce
manual effort and improve process efficiency.



Module 6: Machine Learning Model for Predictive and Prescriptive Modelling



Understand how machine learning can help businesses forecast future outcomes and
evaluate possible actions. This module introduces different machine learning
approaches, their practical applications, and the considerations involved in
selecting suitable models. Learners also explore financial modelling for
planning and budgeting, along with analytics prompting techniques, to understand
how predictive insights can contribute to more informed business decisions.



Module 7: Graphics & Video Generation Using AI



Explore how generative AI can turn ideas and written information into engaging
visual content. Learners practise creating infographics using Copilot Create,
KIMI, and Nano Banana Pro, as well as converting documents into videos using
Copilot Create. These skills can be applied to presentations, training
materials, business communications, and other content where clear visual
storytelling makes information easier to understand.



Module 8: Agent Creation Using Copilot, Gemini Pro, Claude & Custom GPT



Move beyond general-purpose AI conversations and explore the development of
task-specific AI agents. Learners study advanced prompting approaches,
contextual grounding, Copilot Studio capabilities, and custom
retrieval-augmented generation (RAG) agents connected to sources such as
SharePoint and OneDrive. The module also introduces agent evaluation and
grounding techniques, helping learners understand how to build more focused
assistants that use relevant information to produce useful responses.



Module 9: AI Agentic Framework – MCPs, Tools, Triggers & Automation Workflow
with Copilot Studio



Explore how AI agents can interact with tools, access knowledge sources, and
initiate actions through connected workflows. This module covers topics,
variables, conversational flows, conditional triggers, Power Automate
integration, and Model Context Protocol (MCP) servers. Learners develop an
understanding of how these components work together to connect AI agents with
business applications, retrieve information, and support automated processes.



Assignments



The weekly assignments help learners put the concepts covered in class into
practice. Week 1 focuses on personal productivity using Microsoft Copilot and
Microsoft 365 applications. Week 2 moves into AI agents, workflow automation,
and collaborative productivity, while Week 3 covers autonomous AI agents and
advanced Copilot systems. Completing these activities helps learners reinforce
their understanding, test different approaches, and apply their skills to
practical tasks.



Special Class Recordings



Access additional recordings covering Power Apps and Power Automate to
strengthen your understanding of application development and business process
automation. These sessions allow learners to revisit demonstrations, review
important steps, and reinforce techniques that can be used to build applications
and automate routine workflows.



Case Studies, Q&A, Presentation & Internship



Connect the concepts covered in the program with practical business
applications. This section includes industry case studies, success stories, live
Q&A sessions, internship projects, and opportunities to present completed work.
Learners can develop agents, create personas and prompt libraries, and
demonstrate solutions for real business processes. These activities encourage
practical problem-solving and help learners explain and present their work with
greater confidence.



Microsoft Copilot Agent – Development & Deployment



Follow the key stages involved in creating and preparing AI agents for use. The
resources cover development environments, the Copilot Studio interface, topic
creation, agent testing, performance analysis, and publishing. Learners can also
explore examples such as a Risk Analyst Agent, Lesson Plan Generator, and HR
Agent to understand how agents can be designed around specific business needs
and responsibilities.



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