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In this course, you'll learn how to effectively communicate with AI systems to achieve consistent, high-quality results. Whether you're a professional looking to enhance your workflow, a creator seeking to leverage AI tools, or simply curious about this emerging field, this course will provide you with the skills and understanding you need to start engaging with these tools today.
The concept of prompt engineering may sound daunting or complex, but it isn't as scary as you think it is. Simply put, the term "prompt engineering" describes the experience of having an instant messaging chat conversation with a machine to achieve an outcome. The outcome can be anything - from planning your next date night, to creating a social media graphic, to summarizing a dense report. Anyone with an internet connection can use these tools but, to actually achieve your desired result, you need practice.
Imagine that you are working with an assistant who knows everything on entire Internet, can reason like a supercomputer, and can transform anything into anything else. Pretty cool, right? There's only one catch - this assistant is extremely literal and will only give you answers based on the information you've provided to it. You need to provide this assistant with information to do their job. This information can be provided all at once (not as effective) or iteratively (more effective).
Approaching this iteratively (through multiple messages, or a conversational exchange) will always result in a better outcome. Because your assistant is able to go back-and-forth with you (prompting you), they will be able to understand more about what you are trying to achieve. This dialogue is the essence of prompt engineering - combining the art and science of using written human communication to create.
Think of it this way: if traditional programming tells a computer exactly what to do using a set of pre-defined instructions, prompt engineering is like having the ability to update, change, and improve these instructions based on the feedback/output the computer provides. Over time, you'll be able to develop extremely complex solutions with the help from your generative AI assistant as long as you can provide it with 2 things: context and instruction.
The journey to today's AI assistants has been long and fascinating. Everything began with Alan Turing. Widely considered to be the father of modern-day computers, Turing devised a theory that drove the research and innovation that continues today. Initially, computers could only follow rigid, pre-programmed instructions. They were like very fast calculators – great at math, but unable to understand or generate human language. Think about early spell-checkers: they could tell you if a word wasn't in their dictionary, but they couldn't suggest better ways to phrase your sentence or understand what you were trying to say. This continued for decades.
Generative AI changed everything. Instead of just following fixed rules, these systems can create new content – writing, images, code, or music – based on their training. It's like the difference between a calculator and a creative collaborator. When you use tools like ChatGPT, Claude, or Midjourney, you're working with generative AI.
The "generative" part means these systems can produce new, original content rather than just selecting from pre-written responses. They can:
"NLP "stands for Natural Language Processing. This is how AI understands human language. It breaks down your messages into meaningful pieces that it can apply to any presented problem. Think of it as the AI's "ears and brain" for understanding what you're saying. When you type "Write me a poem about a sunset," NLP helps the AI understand you want poetry about a specific topic
"LLM" translates to Large Language Model. These are the powerhouses behind the scenes. They've learned patterns from vast amounts of text and use this knowledge to help them generate relevant, contextual responses. Think of them as having read millions of pieces of content. When you ask for the sunset poem, the LLM uses its understanding of poetry, sunsets, and language to create something new
When you're prompt engineering, you become the conductor, orchestrating these technologies in harmony to create something brand new! Each time that you submit a response within your tool of choice, your prompt becomes the guide within the process, helping the AI know exactly what you want. Then, the conversation becomes a collaboration between human creativity and AI capability:
This is why prompt engineering is so powerful – you're not just giving commands to a computer; you're engaging with a sophisticated system that can understand context, generate new content, and refine its output based on your guidance.
But what does this look like in practice? How do you actually have these conversations with AI? Let's begin to explore some real examples and see prompt engineering in action.
