Mastering AI & Prompt Engineering
Learn how to work effectively with AI - no technical background required. Discover practical skills that will help you get better results with any AI tool.
Learning Modules
Introduction to AI & LLMs
Understand the foundations of AI, machine learning, and large language models in simple terms.
What is Artificial Intelligence?
Artificial Intelligence might sound intimidating, but at its core, it's about teaching computers to learn patterns and make decisions similar to how humans do. Large Language Models (LLMs) are a specific type of AI that focuses on understanding and generating human language.
AI is Already Part of Your Daily Life
You're already using AI every day! From email spam filters and navigation apps to music recommendations and text autocorrect - these are all powered by AI working behind the scenes to make your life easier.
LLMs Understand Context, Not Just Words
Unlike older technologies that simply matched keywords, LLMs understand the meaning behind your words. This is why they can have conversations that feel natural and human-like, rather than robotic responses.
You Don't Need to Be Technical
Using AI tools like ChatGPT, Claude, or Google Gemini doesn't require coding knowledge or technical expertise. If you can have a conversation or write an email, you already have all the skills you need to start using AI effectively.
LLMs are AI systems trained on vast amounts of text from books, articles, websites, and other sources. They learn patterns in language that allow them to:
- Answer questions in natural, conversational language
- Summarize long documents into key points
- Generate creative content like stories or poems
- Translate between languages
- Help brainstorm ideas or solve problems
What is a key advantage of modern AI systems like LLMs?
Prompt Engineering Basics
Learn how to communicate effectively with AI - no technical skills required.
The Art of Asking Good Questions
Prompt engineering might sound complex, but it's simply the art of asking good questions. Just like you might rephrase a question when talking to a person who misunderstood you, learning to communicate clearly with AI helps you get better results.
Think of AI as a Helpful Assistant
AI works best when you treat it like a helpful but literal-minded assistant. Being clear about what you want, providing necessary context, and giving examples all help the AI understand your needs better.
You Can't Break It
Don't worry about asking the 'wrong' question or making mistakes when using AI. Unlike complex software, there's no syntax to learn. If you don't get the result you want, you can simply rephrase your request or give feedback.
Be Specific
"Write a blog post about dogs" will give generic results. "Write a 500-word blog post about training senior rescue dogs, focusing on gentle exercise routines" will give much better results.
Provide Context
"I'm a small business owner creating content for social media to reach local customers" gives the AI important information about your needs and audience.
Ask for Format
Specify the format you want: "Give me this information as a bullet-point list" or "Write this in the style of a friendly email" helps shape the response.
Which approach will likely get the best results from AI?
Advanced Techniques
Take your AI prompting skills to the next level with these powerful strategies.
Taking Your AI Skills to the Next Level
Once you've mastered the basics of prompt engineering, you can explore more advanced techniques to get even better results from AI systems. These approaches can help you tackle more complex tasks and get more precise, creative, or specialized outputs.
Chain of Thought Prompting
Ask the AI to 'think step by step' when solving complex problems. This technique dramatically improves reasoning abilities by encouraging the AI to break down its thinking process, similar to how humans solve difficult problems.
Few-Shot Learning
Provide a few examples of the pattern you want the AI to follow. For instance, if you want a specific format for patient case summaries, show 2-3 examples of that format before asking for a new one.
Role Prompting
Ask the AI to adopt a specific perspective or expertise, such as "As an experienced pediatrician..." or "From the perspective of a medical educator..." This helps frame the AI's responses with the appropriate knowledge and tone.
One of the most powerful techniques is to work with AI iteratively:
- Start with a basic prompt to get initial output
- Review the output and identify what needs improvement
- Ask the AI to refine specific aspects ("Make this more concise" or "Add more clinical details")
- Continue this feedback loop until you get the desired result
This collaborative approach often produces much better results than trying to craft the perfect prompt on your first attempt.
Which technique involves showing the AI examples of the pattern you want it to follow?
Responsible Use
Ethical considerations and best practices for using AI in healthcare and academic settings.
Ethical AI Use in Healthcare
Using AI in healthcare and academic medicine comes with important ethical responsibilities. Understanding these considerations helps ensure that AI remains a positive force that enhances your work while protecting patients and maintaining professional standards.
Patient Privacy is Paramount
Never input real patient data or protected health information (PHI) into public AI systems. Even anonymized data can sometimes be re-identified. Use synthetic or fully de-identified examples when discussing medical cases.
Verify AI-Generated Information
AI can make mistakes or present incorrect information confidently. Always verify any medical information, statistics, or citations provided by AI against trusted sources before using them in clinical or academic work.
Maintain Human Judgment
AI should support, not replace, professional medical judgment. Use AI as a tool to enhance your thinking and workflow, but maintain critical thinking and professional responsibility for all decisions.
Educational Content
Creating teaching materials, case studies with synthetic data, and explanations of complex medical concepts for students or patients.
Research Support
Literature reviews, hypothesis generation, and drafting research protocols (always with human verification).
Administrative Efficiency
Drafting emails, summarizing meetings, organizing information, and other non-clinical tasks that free up time for patient care.