Course Introduction
In a world where generative AI is transforming everything from communication to code, prompt engineering has emerged as the single most important skill to control, guide, and optimize the outputs of large language models (LLMs). Whether you’re shaping digital policy in the public sector, driving innovation in a corporate environment, or leading digital transformation across industries, this course gives you the tools to speak the language of machines—with clarity, structure, and purpose.
“Commanding AI” is a hands-on, strategy-focused course designed for professionals who want to go beyond casual AI usage and start directing results. You’ll learn the mechanics behind generative AI models like ChatGPT, explore prompt structures that deliver consistent and high-value outputs, and master the nuances of instructing AI to write, analyze, generate, and solve problems. Through guided exploration in environments like OpenAI Playground and other prompt-based tools, you’ll discover how to craft prompts that are adaptable, scalable, and context-aware.
The course covers everything from foundational concepts to advanced techniques like few-shot prompting, structured output generation, and prompt optimization. Real-world case studies from sectors like governance, business operations, communications, and development work will show how prompt engineering is already driving efficiency and unlocking new capabilities.
By the end of this program, you’ll have the confidence—and the practical skillset—to lead in a world where prompt fluency is becoming as essential as digital literacy. You won’t just use AI. You’ll command it.
Course Modules
Module 1: Foundations of Generative AI and Prompt Engineering
What is Generative AI? What is it not?
How large language models (LLMs) process prompts and generate responses
Why prompt engineering is the interface between human intent and machine intelligence
Module 2: Anatomy of a High-Impact Prompt
The four key elements: context, instruction, input data, and output format
Prompt types: open-ended, guided, multi-step, and scenario-based
Best practices to avoid vague, biased, or misfired outputs
Module 3: Prompt Tuning in Practice (OpenAI Playground & Beyond)
Hands-on with the OpenAI Playground: interface, parameters, tokens, and presets
Tuning creativity, temperature, repetition, and penalties
Designing for predictability vs. exploration
Module 4: Specialized Prompting Techniques
Few-shot and zero-shot prompting strategies
Role prompting, chain-of-thought reasoning, and step-by-step instructions
Generating structured outputs: tables, summaries, checklists, classification
Module 5: AI for Content, Comms, and Decision Support
Use cases: writing reports, briefings, executive summaries, FAQs
Data synthesis and analysis prompts
Drafting communications in different tones, voices, and languages
Module 6: Case Studies in Prompt Impact
Real-world applications across governance, corporate ops, development projects, and leadership
Lessons from good prompts, failed prompts, and “it looked fine until it wasn’t” prompts
Prompt audits: improving clarity, efficiency, and tone
Module 8: Building Your Prompting Toolkit
Creating your prompt library: saving, sharing, and iterating
Integrating prompting skills into your daily workflow
Staying updated: new models, new tools, and futureproofing
Key Takeaways
By the end of this course, participants will:
Understand how generative AI models interpret prompts
Create prompts tailored to specific use cases and domains
Navigate and fine-tune outputs using the OpenAI Playground
Apply prompting techniques to writing, analysis, and coding tasks
Use zero-shot and few-shot learning effectively
Leverage prompt engineering for business, research, and technical applications
Build a reusable prompt library and workflow strategy
Whether you work in government, business, or digital leadership, this course gives you the skills to move from casual user to confident AI collaborator.
The course is available as an institutional workshop for public sector departments, corporate teams, digital transformation leaders, and innovation-focused organizations.
