AI Prompting Essentials

Module 1

Basics of AI and prompt engineering

A practical introduction to AI, generative AI, and large language models (LLMs). Learn how AI systems work, where they can add value in professional settings, and the key considerations for using them effectively and responsibly.

• Explain what AI, generative AI, and LLMs are, and describe how AI models generate responses
• Identify which tasks are well suited to AI and which require human judgment, and select appropriate tools for different scenarios
• Write and refine prompts with clear objectives, context, and output requirements
• Recognize common AI risks, including bias, privacy concerns, and the need for output verification
• Explain concepts such as tokens, context windows, memory limitations, and their impact on model performance
• Compare prompt engineering, fine-tuning, and RAG, and identify suitable use cases for each approach
• Describe multimodal AI capabilities and the types of tasks they enable
• Evaluate AI models and tools based on factors such as capabilities, context length, cost, privacy, and deployment requirements

• ChatGPT
• Claude
• Gemini

Module 2

Prompt engineering

Learn the principles behind effective prompting and how prompt design influences AI outputs. This module introduces common prompt structures, practical prompting techniques, and approaches for working with AI responsibly in professional environments.

• Define prompts with clear goals, context, instructions, and output formats
• Use open-ended, closed-ended, and task-specific prompts appropriately
• Apply zero-shot and few-shot prompting techniques to improve output quality
• Identify and correct common prompting issues, including ambiguity, insufficient context, and overly broad requests
• Evaluate AI-generated outputs and apply basic ethical, privacy, and data-sharing practices when working with AI tools

• ChatGPT
• Claude
• Gemini

Module 3

Best practices for prompt engineering

Explore advanced prompting methods for handling complex tasks and multi-step workflows. Through applied exercises, you'll learn how to improve output quality, structure reasoning processes, and gain greater control over AI-generated results in business and professional contexts.

• Use iterative prompt refinement to improve results through structured feedback loops
• Apply chain-of-thought prompting when step-by-step reasoning is beneficial
• Design prompt chains that break complex problems into manageable stages
• Use Tree of Thoughts techniques to explore, compare, and evaluate multiple solution paths
• Create role-based, style-specific, and markdown-structured prompts tailored to real-world business scenarios

• ChatGPT
• Claude
• Gemini

Optional workshop: How to Communicate Effectively with AI. Build a practical library of prompts for everyday work tasks. By the end of the workshop, you'll have 3-5 reusable prompt templates, including instructions and output formats that can be adapted to different professional scenarios.