Prompt Engineering Bootcamp (Working With LLMs): Zero to Mastery

There’s a lot of excitement around AI these days, and it’s easy to get caught up in it.

But let’s be clear: prompt engineering won’t be a distinct job for most people.

Nonetheless, mastering prompt engineering is a vital skill for the near future.

AI won’t replace you, but someone who knows how to leverage AI to perform your tasks more efficiently might.

Just as you need to know your way around Microsoft Word and Excel to thrive in today’s workplace, familiarizing yourself with LLMs and effective prompting is crucial.

Diving into prompt engineering can unlock career possibilities across all fields. Understanding how to effectively utilize LLMs will make you stand out in a competitive job market.

This course covers prompting through six essential principles:

1. Research-Driven Insights:

This course emphasizes the science of prompting and working with LLMs, steering clear of mere hype.

We’ll look at how elite institutions and companies like OpenAI, Google DeepMind, and Anthropic are enhancing their prompting strategies.

2. Practical Activities and Exercises:

Real proficiency with LLMs comes from hands-on experience! This bootcamp is packed with exercises to help you explore what LLMs are capable of.

3. Structured and Unstructured Projects:

Applying your skills to create something real and functional not only solidifies your knowledge, but also sets you up for real-world applications.

That’s why you’ll find plenty of both guided and unguided projects in our course.

4. Access to Leading LLMs:

This course supports the use of any LLM you prefer, whether it’s free or paid. You’ll also learn how to download and set up open-source LLMs to run on your own device.

5. Advanced Techniques and Tools:

At its core, prompt engineering is straightforward: ask a question and receive an answer!

Yet, our course goes deeper, covering empirically-validated techniques that boost your prompting effectiveness.

You’ll learn how to create mini-programs using just your prompts, which is essential for professional use or powering your AI projects.

6. The Latest Trends and Updates:

The AI field evolves rapidly, with new developments every week. We’re dedicated to continuously updating this course so you’re always on the cutting edge of knowledge.

While other courses might make grand promises, we’re here to keep it grounded.

Our curriculum is focused on equipping you with practical, relevant skills for effectively engaging with LLMs.

Whether you’re looking to improve your productivity, elevate your creative projects, or craft innovative tech solutions, understanding how to write effective prompts is essential.

By signing up today, you’ll also gain entry to our exclusive live online classroom on Discord, where you'll connect with thousands of fellow students, alumni, mentors, and instructors.

What Is Prompt Engineering and Why Does It Matter?

Prompt Engineering is about effectively interacting with AI to enhance its usefulness and accuracy.

Think of it as learning the art of communicating with AI so that even slight adjustments can significantly improve the outcomes from models like ChatGPT, Claude, and Llama.

Why is this important?

Being able to fine-tune your prompts can mean the difference between receiving generic answers and gaining valuable insights.

Whether you’re a developer, marketer, researcher, or an AI enthusiast, mastering prompt engineering allows you to guide the AI in a reliable and imaginative way.

Here’s a Breakdown of What You’ll Learn in This Prompt Engineering Bootcamp:

Let’s get into the specifics of this prompt engineering course:

Section 1: Introduction to Prompt Engineering

We’ll kick things off with a comprehensive understanding of what prompt engineering is and why it matters.

We’ll discuss its purpose, practical uses, and real-world examples, including insights from NASA.

You’ll learn how to critically reflect on the impact of prompt engineering in your life and engage with current topics in the field.

Section 2: Selecting Your LLM

It’s time to choose your preferred LLM, just like James Bond selecting gadgets for his mission.

We’ll guide you through various LLM options, highlighting both free and paid selections.

Expect demonstrations of the specific tools our instructor recommends, including OpenAI Playground, as well as showcasing LLMs’ diverse features.

You can also opt for an open-source LLM for this course and set your workspace accordingly.

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

Before you’ve even mastered prompting, it’s time to dive in!

This approach is intentional, helping you grasp how intuitive LLMs can be (before showcasing their potential challenges).

You’ll jump right into coding a classic Snake Game using your chosen LLM.

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

Now, it’s time to embark on a project without guidance: developing a Tic-Tac-Toe game with an AI opponent using just your LLM.

Section 5: Understanding LLM Mechanics

To work proficiently with LLMs, you first need a grasp of their underlying mechanics. We’ll break it down in a simple, beginner-friendly way—no prior technical knowledge required.

You’ll uncover whether these models are merely guessing words, learn about the groundbreaking Transformer Model that supports this technology, delve into the GPT architecture, and differentiate between base models and their fine-tuned versions.

Interactive exercises will help you visualize the structure of LLMs and grasp their training process.

We’ll also explore the potential link to Artificial General Intelligence (AGI), empowering you to form opinions and discuss AI competently.

Section 6: Our Prompting Framework

We’ll introduce a structured framework to engage with LLMs that you can apply for crafting intricate, well-thought-out prompts.

You’ll also gain access to a "Prompt Library," providing various examples to refine your prompt engineering skills.

Section 7: Prompting Basics - The Setup

In this section, we’ll delve into the art of creating effective prompts.

This covers:

• Grasping the ‘System Message’
• The significance of context for LLMs
• Employing ‘personas and roles’ to shape prompt tone and style
• Engaging in creative exercises such as screenwriting to reinforce these concepts

You’ll also experiment to see how well LLMs can respect confidentiality.

Section 8: Prompting Basics - The Instruction

This segment focuses on how to formulate user messages that LLMs can accurately interpret.

You’ll explore the importance of clarity, specificity, and how to structure data using delimiters while navigating common human limitations to ensure effective prompts.

You’ll start learning empirically-tested techniques like zero, one, and few-shot prompting, as well as chain-of-thought prompting to generate more coherent and context-sensitive AI responses.

Section 9: Guided Project - Create Your Own Career Coach

Ready for another project? This time, you’re creating a versatile Career Coach to assist you in learning Python (or another subject of your choice).

This Career Coach will feature various modes, including:

1. A learning mode utilizing the Feynman Technique
2. A quiz mode generating topic-specific quizzes
3. A challenge mode that creates tailored coding exercises and offers feedback, complete with an XP points system to gamify your learning experience

Section 10: Prompting Basics - The Output

In this section, you’ll focus on how to shape the responses you receive once you hit ‘enter’.

You’ll learn how to influence the length and format of LLM outputs, ensuring they align with your needs.

Practical tasks will guide you in generating organized outputs, like Excel files and flowcharts.

This section will also introduce advanced strategies such as Jailbreaking and Prompt Injection, enlightening you on the boundaries and possibilities of shaping output with prompts.

Section 11: The OpenAI Playground & LLM Hyperparameters

This section delves into fine-tuning the settings that govern language model behaviors.

We’ll start with an introduction to the OpenAI Playground, which lets you manipulate these parameters.

You’ll learn how ‘Temperature’ and ‘Top P’ influence response creativity, along with ‘Frequency and Presence Penalties’ to enhance output relevance, and how ‘Stop Sequences’ manage the flow of AI responses.

This section is crucial for anyone aiming to adjust the LLM for specific tasks and preferences.

Section 12: Prompting with Autonomous Agents (AutoGPT)

In this segment, you’ll discover the next frontier of AI and LLMs: autonomous agents.

These agents require only a single prompt to complete tasks with minimal or no follow-up input.

You’ll learn to set up your own autonomous agent and take on projects such as creating a straightforward website or a Python program to check for palindromes.

Then, you’ll test out autonomous agents on tasks personalized for your career.

This is a must-have section for anyone interested in the future of AI.

Section 13: Working with Open Source Models

Open-source models are rapidly evolving and are nearing the capabilities of closed-source counterparts from top AI firms.

This section starts by outlining the importance and implications of these models in the AI landscape, including the Chatbot Arena Leaderboard where you can compare various models.

Additionally, you’ll learn to utilize LMStudio to download and set up your local open-source LLM, allowing for private use without stringent limitations.

Section 14: Advanced Prompting Strategies

Here, we’ll walk you through proven prompting strategies that enhance LLM utility.

We’ll also introduce relevant research papers that inform these methods, continuously updating this section as new techniques emerge.

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

It’s time for another hands-on project!

You’ve crafted simpler games before, and now you’ll leverage your skills to develop something more ambitious: a Flappy Bird game.

This will require lots of prompting and iteration, but you’ll be thrilled with what you can achieve!

Section 16: Prompt Testing & Model Assessment

Effective prompt engineering hinges on testing and assessing your prompts across different models, as organizations seek prompts and models that ensure reliable outputs.

In this section, you’ll explore a variety of testing and evaluation methods, including code-based and human grading, along with model-based approaches.

We’ll delve into research that discusses the pros and cons of using LLMs as judges for output evaluation. This section is crucial for mastering quality control in your interactions with LLMs.

Ongoing Updates: Like all courses from Zero To Mastery, this program is continuously evolving.

That means it’s consistently updated and expanded, becoming your go-to resource for discovering and learning the latest techniques as you advance in your career.

So, What’s the Verdict?

This course doesn’t just provide you with a random compilation of prompts or make you watch videos without direction, leaving you unsure of what to do next.

Instead, it’s designed to challenge you and elevate you from a beginner to the top 10% of LLM users 💪.

And guess what? You have absolutely nothing to lose.

You can begin your learning journey today, and if the course doesn’t meet your expectations, we offer a 100% refund within 30 days, no strings attached.