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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