Prompt Engineering for Everyone Bootcamp (Udemy.com)
Craft better prompts for ChatGPT, Claude, Gemini, and more - Prompt like a pro in any AI platforms
Created by: Navid Shirzadi
Last updated September 2026
Our take
Based on the ratings of 32,157 students, a sample of their written reviews and the syllabus, as the course stood in September 2026. No course pays to be reviewed.
This is a short beginner course on prompt engineering, about 3.9 hours across 34 lectures and 10 sections. It opens with what prompting is, then gives its biggest early block to prompt types such as zero-shot, few-shot, chain-of-thought and role-based. Later sections cover how language models work, tuning, meta prompting and hallucination. Navid Shirzadi is a research scientist, and the pitch is tool-agnostic, though reviewers say most demos run in ChatGPT. It was last updated in September 2026.
Praise is steady. Reviewers like the clear language, the practical examples and the explanation of what a token is, and several call it a good base for people starting from zero. Meta prompting and the prompt types get named as highlights. The complaints are just as consistent. Several say he repeats himself and takes too long on each point, that the examples are simple, and that there is no end-to-end project. One reviewer found the tuning section is mostly Python used to run prompts. One more wanted more tools than ChatGPT.
Among 32,157 ratings, about 48 percent are five stars and 41 percent are four, so this is a solid but basic course, not a standout one. At under four hours it is easy to finish, and a certificate comes with it. Anyone already writing structured prompts at work will likely find it thin. Newcomers who want the vocabulary and a few reliable habits will get that. Expect to skim some repeated explanations, and one reviewer says the subtitles need cleanup.
Pros
- Explains tokens and how language models work in plain terms newcomers follow
- Prompt types section (zero-shot, few-shot, chain-of-thought, role-based) is praised as useful
- Meta prompting gets praise, and a dedicated section covers reducing hallucinations
- Only 3.9 hours, with no coding or AI background required
Cons
- Instructor repeats points and talks long on each topic, per several reviewers
- Examples are simple, with no end-to-end project or real-world build
- Demos mostly use ChatGPT, and one reviewer found the tuning section was mainly Python
I liked that he explained what a token is and is not, as I saw them in another training and had no idea what they were.
Truly beginner-friendly with no coding needed, though the optional model architecture and Python parts lean technical.
What you will learn
- Understand what prompt engineering is and why it’s critical to effective AI use
- Explain how large language models (LLMs) like ChatGPT generate responses
- Use core prompting types: zero-shot, few-shot, chain-of-thought, role-based, and more
- Craft clear, structured, and context-rich prompts for a wide range of tasks
- Iterate, test, and refine prompts for improved accuracy and performance
- Recognize and reduce AI hallucinations through strategic prompting techniques
- Apply meta prompting to design better prompts with the help of the model itself
- Optimize prompts for different goals — summarization, content generation, coding, Q&A, etc.
- Apply best practices for ethical and responsible use of AI systems
Course content
10 sections · 34 lectures · 3.9 hours of video 2 articles
- 1Introduction 1 free preview3 lectures · 10 min
- 2Introduction to Prompt Engineering 2 free previews3 lectures · 14 min
- 3Prompting Types 1 free preview9 lectures · 41 min
- 4Understanding Large Language Models3 lectures · 20 min
- 5Deeper into LLMs (Advanced-Optional)2 lectures · 21 min
- 6Crafting Effective Prompts3 lectures · 18 min
- 7Prompt Tuning and Optimization3 lectures · 55 min
- 8Meta Prompting4 lectures · 34 min
- 9AI Hallucination3 lectures · 18 min
- 10Bonus Section1 lecture · 1 min
Who it is for
The instructor says it suits
- Educators designing personalized content, study guides, or AI-powered tutoring
- Professionals looking to automate tasks, boost productivity, or improve communication with AI tools
- Developers and data analysts aiming to integrate prompting into their workflows
- Business teams using LLMs for knowledge management, customer support, and operations
- Students who want to use AI for studying, research, writing assistance, or academic productivity
- Anyone curious about how to talk to AI more clearly, effectively, and safely
What you need before you start
- This course is designed to be accessible to everyone — no coding or AI background required.
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.5 out of 5higher than 45% of them
- Reviews32,157#8 of 1,183 by number of reviews
- Length3.9 hoursshorter than 62% of them
- Last updatedSeptember 2026more recently than 90% of them
Course Description
Prompt engineering is one of the most in-demand and future-proof skills of the AI era — and this course will teach you how to master it.
This hands-on, tool-agnostic course is designed for professionals, educators, developers, analysts, and creatives who want to harness the full potential of large language models (LLMs) like ChatGPT, Claude, Gemini, and others. Instead of treating AI like a black box, you’ll learn how to collaborate with it by crafting structured, context-aware prompts that generate accurate, useful, and safe outputs.
The course starts with foundational concepts — what prompt engineering is, why it matters, and how different types of prompts (zero-shot, few-shot, chain-of-thought, role-based, etc.) impact outcomes. You’ll gain a working understanding of how LLMs generate language, what “tokens” are, and why they sometimes hallucinate or fail to follow instructions.
From there, we dive into real-world strategies for designing effective prompts. You’ll learn how to give the model the right amount of context, test and tune your prompts, and even use meta prompting — prompting the model to help you design better prompts. Each concept is reinforced with practical examples and guided exercises across domains like education, healthcare, legal, marketing, software development, and data science.
You’ll also explore advanced concepts like prompt tuning, hybrid prompting, and ethical AI use — including how to minimize bias, avoid harmful content, and ensure privacy. The course finishes with a capstone module on hallucination reduction, where you’ll learn how to prompt the model in ways that reduce false or fabricated outputs.
No programming background is required, though technically-inclined learners will find optional advanced modules on model architecture (e.g., Transformers) and prompt optimization techniques.
What You’ll Learn:
Core principles of prompt engineering
How LLMs work and why prompt structure matters
Types of prompting strategies and when to use them
How to iterate, test, and refine your prompts for better performance
Using meta prompting to build better prompt templates
Reducing hallucination and guiding the model toward factual accuracy
Ethical use of AI in real-world applications
Prompting for different modalities (text, code, image)
Who This Course Is For:
Professionals who want to automate tasks, improve workflows, or build AI-integrated tools
Educators designing personalized learning materials or AI-assisted content
Writers, marketers, and designers looking to collaborate with AI creatively
Developers and data analysts seeking reliable, repeatable prompts for technical work
Anyone who wants to use AI more safely, effectively, and intentionally
Instructor Details
- 4.5 Rating
32,157 Reviews
Navid Shirzadi
Welcome! I'm Navid Shirzadi, and I'm thrilled that you've taken the time to visit my profile.
As a research scientist, I hold a doctoral degree in engineering and boast over ten years of invaluable experience in the fascinating realm of controlling integrated energy systems. My expertise lies in employing mathematical optimization strategies to tackle complex challenges within this field.
I am well-versed in Python programming and proficient in developing cutting-edge machine learning and deep learning models for various applications. My contributions to the field have been recognized through numerous publications centered around the design and implementation of intelligent control strategies for energy systems, utilizing the power of machine learning, deep learning, and artificial intelligence.
In essence, my passion lies in the realm of Data Science and Machine Learning, and I find immense satisfaction in applying optimization techniques to solve real-world problems. I genuinely look forward to sharing my knowledge and experiences with you!
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Reviews
By Ana Soledad Perez on 8/18/2026
Me parecio super interesante, estoy empezando a trabajar como analista de datos y me preocupaba que la IA tomara mi rol dentro de algun tiempo, justamente por eso quise empezar a aprender a "dominar" a la IA, este curso introductorio es excelente y espero poder seguir estudiando para poder seguir perfeccionandome.
By Smita D Chawla on 8/11/2026
Very new content. great explanations using examples. Loved the types of prompts and meta prompting. Using backend might be good for developers but good to learn. thank you for such amazing and insightful content
By Shawn Wilson on 8/5/2026
Course was as expected and open my eyes on different techniques and ways to improving promoting. I would recommend this course as a refresher or to learn more granular prompting details. Great job!
By Jeanette Jones on 7/28/2026
not much taught in first session re prompt engineering not clear, as someone learning from scratch the sessions are very short and not full of examples and i feel rushed. also prompt engineering is used mainly on creating AI and the examples given are being given on chatGPT, this is a tool most people use every day.
By Conor M Mcelhinney on 7/21/2026
I enjoyed this course apart from the coding bit. Most people will never use that coding part so it may be worth removing it. it also might scare people away from continuing the course.
By Ravi Krishnamoorthy on 7/4/2026
As I progress through the course, I am starting to understand the concepts better, learn new topics, relate it to my daily business/personal use, am enjoying learning. Now that I am almost halfway through, learning is getting bigger and better - first time ever, I got to know how the LLMs generate the desired outputs after learning about the transformer, its layers, etc. The flowchart was very helpful to understand it better.
By Sumita Killamsetty on 7/1/2026
Instructor knows lots of things. He is explaining from basics. He has done a lots of research on AI, LLMs, prompts. The course is well structured. I don't wanted to skip a single lecture.
By Rangana Das on 7/1/2026
The course is content-rich and informative; however, adding deeper practical context, case studies, and advanced learning elements would significantly enhance the learner experience and business value.
By Andrey Podolskiy on 5/28/2026
That cause is part of our internal AI learning path and I found it a bit monotonous at times and repetitive in some areas, when author just repeats same statement few times over and over again. Overall impression is okay, found some useful information for myself.
By Yves Van Tente on 5/14/2026
Really appreciated how the teacher explains carefully what and how you need to install on your computer. Very often teachers take it for granted that you know. So very well done this course. Enjoyed watching it and obviously I have learnt a lot.
Quality Score
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Overall Score : 90 / 100












