The world is buzzing with AI hype. And it’s easy to get swept up.

But here’s the real talk: prompt engineering isn’t a standalone career (at least for the vast majority of people).

However, prompt engineering is a critical skill set that you will need to know in the years to come.

AI isn't going to take your job... but someone that knows how to use AI to do your job better, faster, and more effectively, will take your job.

Just like you need to know how to use Microsoft Word and Excel to work in the modern office environment, you'll need to know how to prompt and work with LLMs.

Learning prompt engineering will open doors to opportunities in every career. And learning how to properly work with LLMs will ensure you set yourself apart from people you're competing for jobs with.

This course teaches prompting based on 6 core principles:

1. Empirical Research and Peer-reviewed Studies:

This course is focused on the science behind prompting and working with LLMs, not the hype.

So we'll explore what AI researchers at leading universities and companies like OpenAI, Google DeepMind, and Anthropic are doing to improve and implement their own prompts.

2. Hands-on Demos and Exercises:

You can't actually learn to work with LLMs unless you actually, well, work with 'em! That's why this bootcamp is filled with exercises that allow you to get your hands dirty and test the limits of what LLMs can do.

3. Guided and Unguided Projects:

Putting your skills into practice and building something real - something useful - not only feels great, but it's the best way to solidify your knowledge and allow you to apply it to your own real-world scenarios.

That's why this course has numerous guided and unguided projects that allow you to do just that.

4. Opportunity to Use Leading Closed- and Open-source Models:

This course is designed to allow you to use whatever LLM you prefer, whether free or paid. You'll even be shown how to download and setup your own open-source LLMs that run locally on your computer.

5. Advanced Tools and Techniques:

Prompt engineering at its core is very basic: ask a question and get an answer!

But this course goes far beyond the basics, so that you'll learn empirically-validated techniques that will increase the utility and effectiveness of your prompting.

This will allow you to create mini-computer programs using nothing but natural language (a prompt). This is vital if you're using LLMs for work or to power your own AI applications.

6. The Latest Information and Updates:

The AI world is advancing rapidly, with new information every week. We're committed to constantly updating this course so that you're learning the latest information and can stay on the cutting edge.

While some courses out there might promise the moon, we’re here to keep it grounded.

Our course is designed to arm you with practical, no-nonsense skills needed to interact effectively with LLMs.

Whether you're aiming to boost your productivity, enhance creative projects, or develop smarter tech solutions, understanding the nuances of crafting prompts is key.

By enrolling today, you’ll also get to join our exclusive live online community classroom on Discord where you'll learn alongside thousands of students, alumni, mentors, TAs and Instructors.

What Is Prompt Engineering and Why Is It Useful?

Prompt Engineering is the skill of communicating effectively with AI to maximize its utility and accuracy.

Think of it as teaching you to be an AI-whisperer, to speak in a language where seemingly small changes can radically alter the quality of outcomes you get from Large Language Models like ChatGPT, Claude, and Llama.

Why does this matter?

Because the ability to fine-tune your interactions can be the difference between getting a generic response and unlocking truly valuable insights.

Whether you’re a developer, a marketer, a researcher, or simply an AI enthusiast, mastering prompting allows you to steer the AI more reliably and creatively.

Here's What This Prompt Engineering Bootcamp Course Covers:

Let's dive into the details of exactly what you'll learn in this prompt engineering course:

Section 1: Introduction to Prompt Engineering

We'll start with an in-depth look at the definition and significance of prompt engineering.

We'll explore the reasoning behind its existence, practical applications, and real-world case studies, including how NASA applies it.

You'll learn to critically assess the role prompt engineering plays in your life and interact with current discussions in the field.

Section 2: Choose Your LLM

It's time to choose your LLM. This is like when James Bond visits Q and gets to choose which high-tech gadgets he'll use for his mission.

We'll walk through your options for using leading LLMs, including giving you the ability to choose free or paid options.

You'll watch demonstrations of the tools the instructor prefers, including the OpenAI Playground. The section also covers the diverse capabilities of LLMs, including multimodal features.

You also have the option to choose to use an open-source LLM for this course and get your workspace setup to do just that.

Section 3: Guided Project - Build Your First Game (Snake Game)

You haven't even learned how to prompt yet, but it's already time to get your hands dirty!

This is strategic - we want you to get a feel for how these LLMs work, how intuitive they can be (before teaching you how unintuitive they can be!).

So you'll dive head-first into coding your very own classic Snake Game using your LLM of choice.

Section 4: Unguided Project - Build Your Second Game (Tic-Tac-Toe with AI Opponent)

It's time to take your training wheels off and let you build a game without guidance, by coding a Tic-Tac-Toe game with an AI opponent using only your LLM.

Section 5: How LLMs Work

In order to truly work with LLMs effectively, you need to understand how they actually work under-the-hood. So we'll explain it all in a beginner-friendly manner, no technical expertise required.

You'll investigate whether these models are word guessing machines, learn about the breakthrough Transformer Model that enables this technology, the architecture behind GPT, and compares base models with their fine-tuned counterparts.

Then you'll work through engaging exercises to help you visualize LLM architecture and understand the training process.

We'll even touch on the potential bridge to Artificial General Intelligence (AGI) so that you'll be able to form your own opinions and discuss AI confidently.

Section 6: Our Prompting Framework

We'll take a structured approach to engaging with LLMs by introducing the framework which we'll be learning, and which you can use to approach crafting detailed, comprehensive prompts.

Plus you’ll have access to a "Prompt Library," a resource filled with a variety of prompts, equipping you with practical examples to enhance your own prompt engineering skills.

Section 7: Prompting Fundamentals - The Setup

This is where we'll deep dive into how to craft effective prompts.

This includes:

• Understanding the 'System Message'
• The importance of context within LLMs
• The concept of 'personas and roles' to refine the tone, style, and voice of prompts
• And provides creative exercises like writing a screenplay to apply these concepts

You'll even put your new skills to the test by exploring the limits of LLMs' abilities to maintain confidentiality.

Section 8: Prompting Fundamentals - The Instruction

This section takes a close look at crafting user messages that LLMs can interpret with precision.

You'll learn about the importance of clarity and specificity, and how to use delimiters to structure information, how to overcome the limitations of humans (yes, we have them too!) to ensure your prompts are effective.

You'll start learning empirically-validated prompting techniques as well, including zero, one, and few-shot prompting an chain-of-thought prompting to achieve more coherent and contextually aware responses from AI.

Section 9: Guided Project - Create Your Own Career Coach

Time for another project! And this one's the coolest yet.

You'll use all the skills that you've learned about so far to construct a single, comprehensive prompt that creates your own personalized Career Coach to assist you in learning Python (or whatever subject you prefer).

This Career Coach involves various modes that can be invoked, including:

1. A learning mode that teaches you using the Feynman Technique
2. A quiz mode that generates quizzes on the same topic
3. A challenge mode that generates personalized coding challenges and provides feedback on your answers, and even introduces an XP points system to gamify and motivate your learning

Section 10: Prompting Fundamentals - The Output

This section focuses on what comes after you hit 'enter': the model's response.

You'll learn how to manage and influence the length and format of LLM outputs, ensuring they meet your specific requirements.

Practical exercises will guide you through generating structured outputs, such as Excel files and flowcharts.

The section also delves into advanced techniques like Jailbreaking and Prompt Injection, teaching you the limits (good and bad) of how users can shape the nature and direction of outputs.

Section 11: The OpenAI Playground & LLM Hyperparameters

This section is all about tweaking the dials and switches that control the behavior of language models.

It kicks off with an introduction to the OpenAI Playground which will allow you to control these dials and switches.

You'll learn about 'Temperature' and 'Top P' settings to adjust the creativity and determinism of responses, as well as 'Frequency and Presence Penalties' to refine output relevance, and the use of 'Stop Sequences' to manage where and when AI responses should end.

This section is key for anyone looking to tune the LLM to their specific tasks and preferences.

Section 12: Prompting with Autonomous Agents (AutoGPT)

Here you'll learn about the future of AI and Large Language Models: autonomous agents.

These agents allow you to input a single prompt and then go off to accomplish your task with limited or no further prompting.

You'll learn to set up your own autonomous agent and then accomplish tasks such as creating a simple website and developing a Python program to check for palindromes.

Then you'll test out autonomous agents at a task of your own choosing, that's relevant for your own career.

This is a can't-miss section or anyone wanting to understand the future of AI.

Section 13: Using Open Source Models

Open source models are growing rapidly and approaching similar capabilities as closed-source models from leading AI companies like OpenAI and Anthropic.

This section will begin by explaining the significance of these models and their impact on the AI field, including the Chatbot Arena Leaderboard where you'll get to pit different models against each other.

But that's not all. You'll also learn to utilize LMStudio to download and setup your own open source LLM locally on your computer, which will allow you to use an LLM without worrying about sharing private information, without strict guardrails, and without rate limits.

Section 14: Advanced Prompting Techniques

This section contains step-by-step processes to using some of the leading, empirically-proven prompting techniques to improve the utility of the LLMs.

We'll even dive into the research papers that discovered these techniques. Plus, this section will be continually updated and expanded as new techniques are discovered.

Section 15: Unguided Project: Build Your Third Game (Flappy Bird)

It's once again time to get your hands dirty!

You've already built some simple games using code generated by LLMs, but now it's time to put all your skills to use and create something more complex: a Flappy Bird game.

This will require significant time and iteration of prompting, but you'll be amazed at what you can achieve with your skills.

Section 16: Prompt Testing & Model Evaluation

Being effective at Prompt Engineering means being able to test your prompts and evaluate what works best across various models. That's becuase companeis are looking for prompts and models that provide reliable outputs.

In this section you'll explore various testing and evaluation methodologies including code-based grading, human grading, and model-based grading.

Plus we'll dive into the research showing the pros and cons of LLMs serving as judges in evaluating outputs. This section is essential for anyone looking to master the quality control aspects of working with LLMs.

Unlimited Updates: This course, like all Zero To Mastery courses, is a living, breathing thing.

That means it's constantly being updated and expanded so that it'll be your go-to place to find and learn the latest best practices as you develop and grow in your career.

What's The Bottom Line?

This course is not about giving you a random list of prompts or just making you watch some videos so that when you are done with the course you don’t know what to do other than watch another tutorial.

Instead, this course will push you and challenge you to go from a beginner to being in the top 10% of people using LLMs 💪.

And... you have nothing to lose.

You can start learning right now and if this course isn't everything you expected, we'll refund you 100% within 30 days. No hassles and no questions asked.