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Enhancing Productivity with Microsoft Copilot

Course Summary

The Enhancing Productivity with Microsoft Copilot course is designed to transform how professionals interact with the Microsoft 365 ecosystem. Focusing on Outlook, Teams, Excel, and PowerPoint, this course will guide participants through practical, hands-on exercises that will leverage Copilot to automate routine tasks, create professional-quality content, and improve team workflows.

Participants will evolve from the fundamentals of Copilot, understanding how it integrates seamlessly into their daily work to boost efficiency. Through a blend of technical lecture and hands-on laboratory exercises, participants will gain the skills to automate repetitive data analysis, streamline complex communications, and apply "Human-in-the-Loop" verification to ensure AI-generated outputs meet professional standards.

Prerequisites:

  • Working knowledge of Microsoft 365 applications with emphasis on Outlook, Excel, and PowerPoint
  • Access to a Microsoft 365 account with an active Copilot license
  • Familiarity with basic data tables and navigating a spreadsheet in Excel

 

Purpose
Gain practical knowledge to integrate the use of Microsoft Copilot in day-to-day work
Audience
Professionals looking to boost their productivity, improve team collaboration, and build confidence in using AI tools to optimize their workflows
Role
Technical and Non-Technical Professionals
Skill level
Beginner
Style
Lecture | Hands-on Activities | Labs
Duration
1 day
Related technologies
Microsoft 365

 

Learning objectives
  • Explain Microsoft Copilot’s underlying AI architecture
  • Apply iterative prompt engineering techniques to generate high-quality content
  • Automate Complex Data Tasks in Excel
  • Streamline Outlook and Teams workflows
  • Execute Cross-App Workflows
  • Evaluate AI-generated outputs for accuracy and bias approach to all automated professional work

What you'll learn:

In this Enhancing Productivity with Microsoft Copilot course, you'll learn:

Introduction to Microsoft Copilot & Copilot Fundamentals

  • Introduction to Microsoft Copilot
  • Core AI-driven features
    • Document generation
    • Summarization
    • Task automation
    • Insights extraction
  • Integrating Copilot with Microsoft 365 to assist in routine tasks
  • Foundations of Prompting

Communication & Workflow Mastery

  • Outlook :Streamlining Email and Calendar
    • Automating Email Drafting and Responses
    • Scheduling and automating meetings, agendas, and sending reminders
    • Inbox Prioritization and AI-Driven Task Management
  • Teams: Improving Collaboration
    • Summarizing key meeting points and automatically assigning tasks.
    • Extracting insights from long chat threads and shared documents
    • Automating project updates and reminders for milestones and deadlines

Data Analysis & Visual Storytelling

  • Excel with Copilot
    • Data Exploration: Identifying outliers, inconsistencies, and trends using natural language
    • Formula Generation: Drafting complex formulas by describing the goal
    • Deep Insights: Generating instant pivot tables and charts from raw data ranges
  • PowerPoint: Design & Creation
    • Generating Slides from Text and Data
    • Improving design: AI suggestions for layouts, fonts, and color schemes
    • Refining storytelling and reorganizing content for effective narratives
    • Generating summary slides and action items from meeting notes

Advanced Practical Applications

  • Cross-Application Workflows:
    • The "Meeting-to-Memo" Pipeline: Converting a Teams transcript into a Word proposal and an Outlook follow-up
    • The "Data-to-Deck" Pipeline: Extracting Excel KPIs to build a 5-slide PowerPoint executive summary
  • Prompt Engineering for Professionals:
    • Iterative refining: Techniques for "nudging" the AI to adjust tone, length, or persona
    • Setting contextual guardrails to ensure professional-grade output
  • Privacy, Ethics, and Verification:
    • Understanding data sensitivity and organizational "tenant" security.
    • The "Human-in-the-loop" requirement: Best practices for fact-checking AI-generated content

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