Prompt Engineering and Generative AI

AI basics

• What AI is, and what it is not
• Machine learning: learning from examples
• Generative AI across text, images, audio, video and code
• AI applications versus AI models
• How large language models work
• Tokens, context and memory
• Hallucinations and how to verify answers

Prompting foundations

• Turning a question into a good prompt
• The five-part formula: Goal, Context, Constraints, Output, Check
• Context and grounding
• Constraints and boundaries
• Asking for the output format you need
• ChatGPT tips and copy-ready prompts

Techniques and tools

• Roles and personas
• Zero-shot, one-shot and few-shot prompting
• Iterative prompting
• Choosing between popular AI tools
• Images, audio, video, music, 3D and multimodal
• Working with files, PDFs and data
• Coding with AI: plan, generate, test, review

Advanced patterns

• Templates and prompt chaining
• Structured prompts and reasoning tasks
• AI agents and tool use, with approval gates
• RAG: retrieve trusted knowledge, then generate
• Evaluating prompts and outputs

Safety and real workflows

• Safety, privacy and responsible AI
• Projects for writing and learning
• Projects for research and decisions
• Everyday connected AI: email, calendar and docs

Your AI workflow

• Define the problem and the user
• Choose a tool or model, and explain why
• Write a five-part prompt template
• Sketch a chain or agent with approval gates
• Design, test and explain a real system

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