AI Prompting-Copilot

AI Prompting-Copilot Courseware (TOS-PRCO)

AIMicrosoft

This Copilot training course delivers a technically grounded introduction to GPT-based AI systems designed for enterprise and professional environments, with emphasis on model architecture concepts, generative AI capabilities, and real-world workflow integration. Participants explore how large language models process and generate text, examine the functional scope and constraints of Copilot Chat, and apply structured prompt-engineering frameworks to optimize output quality, relevance, and consistency. The curriculum extends beyond basic usage to address AI-assisted business communication, knowledge management, and customer service models, highlighting human-in-the-loop collaboration, quality control mechanisms, and decision-support use cases. A dedicated focus on AI ethics and bias mitigation equips learners with governance-oriented strategies, such as verification protocols, contextual prompting, and oversight practices, ensuring responsible deployment at scale. This course is designed to help technical and non-technical stakeholders alike evaluate, implement, and manage Copilot-enabled solutions with confidence, rigor, and operational impact.

Publisher: Tosarion, LLC

Benefits

  • A foundational understanding of AI and GPT-based tools such as Copilot​
  • Practical skills in writing clear, effective prompts to guide AI output
  • Experience using Copilot for professional communication and collaboration​
  • The ability to evaluate AI-generated content for accuracy, clarity, and tone​
  • Awareness of ethical considerations and bias in AI-assisted work​
  • Confidence applying AI tools responsibly within everyday workflows​

Teaching This Course

The publisher has provided details here on how to teach this AI Prompting-Copilot course.

Outline

Module 1: Understanding AI GPT Based Tools

Lecture Outline

  • Introduction: AI in Contemporary Society
    Key definitions, historical evolution, and current applications across industries.
  • Foundations of Generative AI and GPT Models
    Model architecture overview, training concepts, and limitations.
  • Overview of AI Platform (Copilot ChatGPT)
    Analysis of capabilities, suitability for tasks, and real-world usage contexts.
  • Integrating AI into Professional Workflows
    Practical considerations, productivity enhancement, and decision-support potential.
  • Summary and Conceptual Takeaways
    Reinforcement of terminology and essential model characteristics.

Module 2: The Power of Prompt Engineering

Lecture Outline

  • Introduction to Prompt Engineering Principles
    Why prompts matter; relationship between user intent and AI interpretation.
  • Structure of Effective Prompts
    Role definition, constraints, tone guidance, and contextual detail.
  • Analytical Review: Good vs. Poor Prompt Characteristics
    Theory-based examples (no live demonstration); analysis of clarity, specificity, and utility.
  • Prompt Revision Framework
    Guidelines for systematic refinement to improve results.
  • Lecture Summary and Preparation for Lab
    Overview of how learned principles will be applied.

Module 3: Copilot Chat for Business Communication Collaboration

Lecture Outline

  • Copilot Chat Assistance for Team Workflows
    Meeting summaries, documentation support, and knowledge-base structuring.
  • Copilot Chat in Customer Service Theory
    Ticket categorization, conversational tone guidelines, escalation logic.
  • Human-AI Collaboration Model
    When to rely on AI, when humans intervene, and strategies for quality assurance.
  • Lecture Review and Lab Preparation
    Outline of how theoretical concepts translate into simulated activities.

Module 4: Ethics Bias Awareness in Copilot Chat

Lecture Outline

  • Introduction to AI Ethics for Copilot Chat
    Fairness, accountability, transparency frameworks, and privacy considerations.
  • Understanding AI Bias related to use of Copilot Chat
    How training data, model design, and context influence biased results.
  • Case Study Analysis (Conceptual Only)
    Review written examples of biased outputs; theoretical root-cause identification.
  • Bias Mitigation Strategies
    Verification protocols, prompt techniques, and oversight mechanisms.
  • Recap and Preparation for Lab
    How lab activities will reinforce ethical evaluation skills.

Required Prerequisites

Basic computer skills.

License

Length: 1 day | $35.00 per copy

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What is Included?
  • Student Manual
  • Extra Trainer Files
  • PowerPoint Presentation