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

Stop memorizing random prompts. Instead, learn how Large Language Models (LLMs) actually work and how to use them effectively. This course will take you from beginner to mastering LLMs by teaching you how to create your own AI tools that will take your career to the next level.

24 Days

Average time students take to complete this course.

instructor
Taught by: Scott Kerr
Last updated: June 2024

Course overview

Learn how to work with LLMs and AI. We guarantee you that this is the most comprehensive and up-to-date prompt engineering bootcamp course. You're going to learn the skills needed to be in the top 10% of using AI in the real world.

What you'll learn

  • Learn the fundamentals of prompting and its practical applications, including real-world examples from NASA
  • Gain practical experience and a deeper understanding of how LLMs work (and how they don't) through hands-on exercises
  • Learn to use leading closed-source LLMs like GPT and Claude and even set up your own open-source LLMs
  • Master empirically-proven prompting techniques to improve the effectiveness and utility of your interactions with LLMs
  • Apply your skills in real-world scenarios through numerous guided and unguided projects that teach you to apply your skills
  • Stay updated with the latest advancements in AI and prompt engineering, with continuous course updates to ensure you are always at the cutting edge

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.

When's the best time to get started? Today!

There's never a bad time to learn in-demand skills. But the sooner, the better. So start learning to work with LLMs today by joining the ZTM Academy. You'll have a clear roadmap to writing effective prompts, building your own AI apps, and advancing your career.

Join Zero To Mastery Now

What you'll build

The best way you learn is by doing. Not just watching endless tutorials. That's why a key part of this course is building your own prompts and projects using LLMs.

Snake Game

Snake Game

Use your LLM to code a simple Snake Game and modify it to your own preferences.

Tic Tac Toe (w/ AI opponent)

Tic Tac Toe (w/ AI opponent)

Use your LLM to develop a Tic Tac Toe game with an AI opponent for the user to play against.

Create Your Own Career Coach

Create Your Own Career Coach

Develop a comprehensive prompt that creates your own personalized Career Coach, utilizing various modes that can be invoked to teach using the Feynman Technique, quiz you, create coding challenges with feedback, and even XP points to gamify your learning.

Autonomous Agents

Autonomous Agents

Learn about where LLMs are going by setting up your own autonomous agent and have them generate a Hello World website, create a Python program that checks for palindromes, and even initialize the agent for your own work-related task.

Flappy Bird

Flappy Bird

Time to code your most advanced game yet using only an LLM: a Flappy Bird game. This will require you to put all the skills you've learned so far to work, and will require iteration and working with the LLM to debug.

Prompting Research and Evaluation

Prompting Research and Evaluation

One of the most exciting parts about this field is that there's always new prompt techniques being discovered and research being released. You'll learn to hypothesize, develop and test your own prompting technique, as well as evaluate various models.

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Course curriculum

To make sure this course is a good fit for you, you can start learning about prompting for free right now by clicking any of the PREVIEW links below.

Section 0: Introduction

6 lectures

Learn To Work With LLMs with Scott Kerr1:00

PREVIEW

Course Introduction6:19

PREVIEW

Course Resources + Handbook

BEGIN

Exercise: Meet Your Classmates and Instructor

PREVIEW

ZTM Plugin + Understanding Your Video Player

PREVIEW

Set Your Learning Streak Goal

PREVIEW

Section 1: Introduction to Prompt Engineering

9 lectures

What is Prompt Engineering?6:24

BEGIN

Why is Prompt Engineering Even a Thing?8:31

BEGIN

Breaking GPT4:02

BEGIN

Applied Prompt Engineering4:24

BEGIN

Applied Prompt Engineering with NASA9:29

BEGIN

Why is Prompt Engineering Important to You?4:06

BEGIN

The Latest: Am I Wrong?

BEGIN

Homework: AlphaGo

BEGIN

Let's Have Some Fun (+ More Resources)

BEGIN

Section 2: Choose Your LLM

5 lectures

What I'm Using - Part 11:21

BEGIN

What I'm Using - Part 2 (OpenAI Playground)4:02

BEGIN

Optional: Setting Up Your Playground

BEGIN

Multi-Modality and Tools in LLMs11:41

BEGIN

Choose Your LLM!

BEGIN

Option A (Recommended & Free Option): ChatGPT (GPT-4o) Setup

4 lectures

Getting Started with ChatGPT1:39

BEGIN

The Basics of ChatGPT4:08

BEGIN

ChatGPT App1:11

BEGIN

Optional: ChatGPT Plus1:55

BEGIN

Option B (Open Source & Free Option): Llama Setup

1 lectures

Getting Started with Llama

BEGIN

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

8 lectures

Project Introduction2:13

BEGIN

Setting Up Your Replit Account4:44

BEGIN

Two Important Points

BEGIN

The First Try4:41

BEGIN

Building Our Snake Game - Part 16:12

BEGIN

Building Our Snake Game - Part 25:49

BEGIN

Exercise: Make It Prettier!

BEGIN

Unlimited Updates

BEGIN

Section 4: How LLMs Work

16 lectures

Introduction to LLMs - Part 15:44

BEGIN

Introduction to LLMs - Part 24:11

BEGIN

Tokens5:17

BEGIN

Word Guessing Machines?5:50

BEGIN

Thinking Like LLMs - Roll a Dice6:56

BEGIN

Inside LLMs11:11

BEGIN

The Transformer Model7:38

BEGIN

GPT Meaning

BEGIN

Exercise: Visualize the LLM Architecture3:56

BEGIN

The Training Process9:57

BEGIN

Base Model vs. Assistant Model7:06

BEGIN

Thinking Like LLMs - The Reversal Curse5:14

BEGIN

Artificial General Intelligence (AGI)5:28

BEGIN

Exercise: Use ChatGPT to Read the Research4:48

BEGIN

The World of LLMs6:05

BEGIN

Implement a New Life System

BEGIN

Section 5: Challenge - Build Your Second Game (Tic Tac Toe with AI opponent)

1 lectures

Challenge Instructions

BEGIN

Section 6: Our Prompting Framework

4 lectures

Overview of Our Prompting Framework3:30

BEGIN

The Standard Prompt4:33

BEGIN

Prompt Library

BEGIN

Exercise: Get Hyped to Learn!4:04

BEGIN

Section 7: Prompting Fundamentals - The Setup

23 lectures

The Setup1:01

BEGIN

The System Message - Part 16:07

BEGIN

The System Message - Part 25:43

BEGIN

Exercise: Strengthen Your System Message6:42

BEGIN

Claude 3's System Message

BEGIN

Context - What it Is5:17

BEGIN

Context - The Context Window9:21

BEGIN

Context - Lost in the Middle11:26

BEGIN

The Latest: Gemini 1.5's Context Window

BEGIN

Personas and Roles8:42

BEGIN

Personas - Tone, Style and Voice11:49

BEGIN

Exercise: Talk To Your Hero

BEGIN

Exercise: Write a Movie Scene

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Custom Instructions11:14

BEGIN

The System Message for Custom Instructions

BEGIN

Thinking Like LLMs - Can GPT Keep a Secret?4:45

BEGIN

Exercise: Get ChatGPT to Spill the Tea - Part 11:44

BEGIN

Exercise: Get ChatGPT to Spill the Tea - Part 21:42

BEGIN

Exercise: Get ChatGPT to Spill the Tea - Part 34:24

BEGIN

Exercise: Test Techniques for Securing Secrets

BEGIN

Exercise: Stump Me!

BEGIN

Case Study: Moderna's Use of ChatGPT

BEGIN

Course Check-In

BEGIN

Section 8: Prompting Fundamentals - The Instructions

17 lectures

The User Message2:09

BEGIN

Be Clear and Specific3:52

BEGIN

Delimiters5:15

BEGIN

Exercise: Identify Delimiters3:25

BEGIN

X-Y Problem6:10

BEGIN

Exercise: Identify X

BEGIN

Solution: Identify X

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In-Context Training1:01

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Zero Shot Prompting1:47

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One Shot and Few Shot Prompting9:48

BEGIN

Language Models Are Few-Shot Learners3:48

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How Many Examples?2:23

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Thinking Like LLMs - But Wait...5:36

BEGIN

Chain-of-Thought Prompting - Part 15:24

BEGIN

Chain-of-Thought Prompting - Part 25:45

BEGIN

Zero Shot CoT9:29

BEGIN

Exercise: Imposter Syndrome2:55

BEGIN

Section 9: Guided Project - Create Your Own Career Coach

8 lectures

Career Coach Ideation7:32

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The Setup - Persona6:02

BEGIN

The Setup - Context and Commands5:42

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The Instructions - Modes12:20

BEGIN

The Instructions - Chain of Thought3:51

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The Instructions - Gamify9:01

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Meet Your Career Coach19:53

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Exercise: Customize Your Career Coach

BEGIN

Section 10: Prompting Fundamentals - The Output

7 lectures

The Output1:35

BEGIN

Length12:33

BEGIN

Formats7:42

BEGIN

Exercise: Output an Excel File2:30

BEGIN

Exercise: Make a Flowchart4:01

BEGIN

Jailbreak!7:25

BEGIN

Thinking Like LLMs - Prompt Injection9:17

BEGIN

Section 11: LLM Hyperparameters & The OpenAI Playground

6 lectures

Introduction to Hyperparameters and the OpenAI Playground3:15

BEGIN

Note: Setting Up Your Playground

BEGIN

Temperature10:25

BEGIN

Top P4:08

BEGIN

Frequency and Presence Penalties4:38

BEGIN

Stop Sequences5:22

BEGIN

Section 12: Guided Project - Prompting with Autonomous Agents (AutoGPT)

11 lectures

Project Introduction

BEGIN

Setup Instructions

BEGIN

Setup Demo: Getting Your API Key2:23

BEGIN

Setup Demo: Downloading AutoGPT1:03

BEGIN

Setup Demo: Installing Docker3:26

BEGIN

Launching Your Autonomous Agent - Part 13:25

BEGIN

Launching Your Autonomous Agent - Part 21:21

BEGIN

It's Aliiiiiive! Running Your Autonomous Agent4:51

BEGIN

Task 1: Hello World - Your First Website16:17

BEGIN

Task 2: Python Program - Palindrome Checker8:40

BEGIN

Task 3: Initialize Your Own Task

BEGIN

Section 13: Open Source Models

10 lectures

What Are Open Source LLMs and Why Are They Important?6:50

BEGIN

Chatbot Arena Leaderboard7:52

BEGIN

Battle of the Intelligence Tests14:38

BEGIN

Exercise: Test The Models With Your Specific Use-Case

BEGIN

Exercise: Create Your Own Test Prompt (Totem)1:35

BEGIN

The Latest - The Best Open Source Model

BEGIN

Introduction to LMStudio2:37

BEGIN

Setting Up Your Own Model - Part 12:51

BEGIN

Setting Up Your Own Model - Part 29:38

BEGIN

Exercise: Explore the Guardrails

BEGIN

Section 14: Advanced Prompting Techniques

25 lectures

Introduction1:06

BEGIN

Auto-Priming10:50

BEGIN

Chain of Density Prompting18:16

BEGIN

Prompt Variables7:13

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Prompt Chaining8:38

BEGIN

Prompt Chaining - Programmatic Visualization17:40

BEGIN

Exercise: Prompt Chaining - Customer Support22:33

BEGIN

Exercise: Create Your Own Prompt Chain!

BEGIN

Thinking Like LLMs - Dark Magic9:57

BEGIN

Exercise: Use Your Magic Powers

BEGIN

XML Tags - There's More Than Meets The Eye!9:17

BEGIN

Emotional Stimuli - Part 118:36

BEGIN

Emotional Stimuli - Part 24:42

BEGIN

Emotional Stimuli - Part 3 (But Why?)7:17

BEGIN

Self-Consistency13:44

BEGIN

Exercise: Implement the Self-Consistency Technique

BEGIN

ReAct Prompting21:34

BEGIN

ReAct + CoT-SC16:47

BEGIN

Applied Prompt Engineering with CRISPR - Part 113:40

BEGIN

Applied Prompt Engineering with CRISPR - Part 214:52

BEGIN

Tree of Thoughts - Part 114:56

BEGIN

Tree of Thoughts - Part 24:56

BEGIN

Tree of Thoughts - Part 3 (ToT via Code)11:33

BEGIN

Tree of Thoughts - Part 4 (ToT via Chaining)22:11

BEGIN

Tree of Thoughts - Part 5 ("Zero Shot" ToT)12:26

BEGIN

What's Next?

1 lectures

Let's Keep Learning & Improving!

BEGIN

Section 15: Challenge - Build Your Third Game (Flappy Bird)

1 lectures

Challenge Instructions

BEGIN

LAUNCHING SOON - Section 16: Prompt Testing and Model Evaluation

1 lectures

Here's What's Coming In This Section

BEGIN

Where To Go From Here?

7 lectures

What's Next?

BEGIN

Thank You!1:17

BEGIN

Review This Course!

BEGIN

Become An Alumni

BEGIN

Learning Guideline

BEGIN

ZTM Events Every Month

BEGIN

LinkedIn Endorsements

BEGIN

Meet your instructor

Your LLM & Prompt Engineering Bootcamp instructor (Scott) is more than just an AI enthusiast. He has years of real-world professional experience. He has been in your shoes. He makes learning fun. He makes complex topics feel simple. He will motivate you. He will push you. And he will go above and beyond to help you succeed.

Scott Kerr

Hi, I'm Scott Kerr!

Scott uses his years of professional research and enthusiasm for AI to teach and guide new students to learn how to utilize AI, get hired and advance their careers.

SEE MY BIO & COURSES

Scott Kerr

Head of AI Initiatives

Frequently asked questions

Are there any prerequisites for this course?

  • None! All you need is an enthusiasm to learn, and you have the option to use paid or free, and closed or open source LLMs.

Who is this course for?

  • Anyone aiming to gain a comprehensive and practical understanding of modern techniques in prompt engineering and LLMs.
  • Developers looking to understand how to work with LLMs that are implemented in their AI-driven applications or within their organizations
  • Graduates of coding bootcamps or online AI courses who wish to delve deeper into the nuances of prompt engineering and explore beyond the introductory concepts
  • Individuals aspiring to integrate AI and LLMs into their career
  • You seek a structured guide to learning how to design effective prompts and interact with LLMs from scratch, progressing to proficiency levels that position you attractively compared to those without AI knowledge
  • Students who find beginner tutorials on LLMs inadequate, as they do not progress beyond basic examples and fail to provide advanced skills
  • Developers eager to transition into AI-focused roles, leveraging the powerful capabilities of LLMs for tasks such as iterating, summarizing, transforming, inferring, and expanding information.
  • You are an AI enthusiast who wants to learn more in a fun, interactive manner

Do you provide a certificate of completion?

We definitely do and they are quite nice. You will also be able to add Zero To Mastery Academy to the education section of your LinkedIn profile as well.

Can I use the course projects in my portfolio?

Yes, you’d be crazy not to in our slightly biased opinion! All projects are downloadable and ready to use the minute you join.

Many of our students tell us the projects they built while following along with our courses were what got them interviews and because they built the projects themselves, they could confidently explain and walk through their work during the interview.

You know what that means? Job offer!

Are there subtitles?

Yes! We have high quality subtitles in 11 different languages: English, Spanish, French, German, Dutch, Romanian, Arabic, Hindi, Portuguese, Indonesian, and Japanese.

You can even adjust the text size, color, background and more so that the subtitles are perfect just for you!

Still have more questions about the Academy?

Still have more questions specific to the Academy membership? No problem, we answer some more here.

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