AI Prompting-Copilot (TOS-PRCO)

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

In this course participants will learn:

• 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​

Module 1: Understanding AI GPT Based Tools

• 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

• 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

• 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

• 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.

Basic computer skills.

*Labs must be purchased from the lab provider.