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Top 7 Udemy Courses to Learn Prompt Engineering in 2025

javinpaul
Sent as aNewsletter
9 min readMay 10, 2025

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Hello guys, as AI taking over the coding world, prompt Engineering is quickly becoming one of the most valuable skills for software developers like you and me.

Whether you’re working with ChatGPT, Claude, Gemini, or any other large language model (LLM), your ability to craft effective prompts directly affects the quality and accuracy of the AI’s response.

As companies, both big and small, from banks to services based companies like TCS and Infosys, increasingly adopt AI tools to boost productivity, the demand for professionals who understand how to communicate effectively with these models is skyrocketing.

But here’s the catch — Prompt Engineering is not just about giving instructions. It’s a hybrid skill that blends creativity, logic, programming literacy, and a deep understanding of how language models work.

Whether you’re a Software developer, web developer, a data analyst, content creator, or product manager, knowing how to structure prompts gives you a competitive edge.

Earlier, I have shared best AI courses, best ChatGPT courses, best Data Science courses and best Machine Learning courses and in this article, I am going to share best Udemy courses to learn Prompt Engineering in 2025.

, with its vast collection of affordable and high-quality courses, is one of the best platforms to start or deepen your prompt engineering journey.

In this post, I’ve curated the 7 best Udemy courses to learn Prompt Engineering in 2025, based on depth, relevance, instructor experience, and hands-on value.

By the way, if you are in rush then you can just go ahead and start with course on Udemy. This is the latest and most up-to-date course on ChatGPT on Udemy.

7 Best Prompt Engineering courses on Udemy in 2025

Without any further ado, here are the best prompt engineering courses you can join on Udemy in 2025

1.

This course is a comprehensive guide not only to ChatGPT and prompting, but also GitHub Copilot.

In this course, you will learn practical coding skills for working professionally with AI, including GPT-4, Stable Diffusion, and GitHub Copilot.

It’s great for learners who want to explore a variety of AI tools and understand how prompt structures differ across use cases.

What you’ll learn:

  • ChatGPT 4 prompt writing techniques
  • Prompting for creative tasks vs analytical tasks
  • Using GitHub Copilot for code generation.
  • AI prompt strategies for entrepreneurs and freelancers
  • Learn the “Five Principles of Prompting”, as well as common tips & tricks for professional grade output.

Here is the link to join this course —

2.

Created by Asif Farooqui, this course focuses solely on mastering the art and science of Prompt Engineering. The instructor emphasizes real-world examples, which makes it highly practical.

What you’ll learn:

  • Prompt templates for different professional use cases
  • How to debug prompts when results go wrong
  • Prompt Engineering ethics and limitations
  • Role prompting and chain-of-thought strategies

Here is the link to join this course —

3.

This is one of the most in-depth courses for developers. It blends theory with applied use cases and includes prompt crafting for software development, product design, and marketing content.

What you’ll learn:

  • Zero-shot, one-shot, few-shot prompting
  • Using ChatGPT with APIs for task automation
  • Prompt strategies for code generation and debugging
  • Building tools on top of GPT-based APIs

Here is the link to join this course —

4.

Perfect for beginners and non-coders. This course focuses on everyday productivity tools powered by AI and how to use ChatGPT for tasks like writing, email automation, summarization, and brainstorming.

Most importantly you will learn to combine the power of ChatGPT with programming fundamentals, algorithms, debugging, and documentation!

What you’ll learn:

  • Prompt frameworks like PASTOR and ACT
  • Best practices for business communication
  • Tools like Notion AI, Google Bard, and ChatGPT
  • Case studies in marketing and HR

Here is the link to join this course —

5.

This one is a very accessible introduction with a step-by-step approach. This course is aimed at complete beginners and teaches you how to think like a prompt engineer.

What you’ll learn:

  • Core building blocks of an effective prompt
  • Structured and iterative prompt techniques
  • Common pitfalls and how to avoid vague outputs
  • Role-based prompting for personas

Here is the link to join this course —

6.

This course is ideal for developers and engineers looking to build LLM-powered apps. It focuses on using LangChain — a framework that allows advanced orchestration of prompts and memory with OpenAI.

What you’ll learn:

  • Prompt templates with LangChain
  • Contextual memory and chaining techniques
  • Integration with OpenAI API
  • Building chatbots and autonomous agents

Here is the link to join this course —

7.

This course targets intermediate to advanced users who want to go beyond simple prompting. It covers the latest techniques like prompt chaining, few-shot learning, and integrating tools with ChatGPT.

It share 1000+ prompts you can use for various things like coding, testing and product development. You will also learn to create thousands of unique prompts for ChatGPT, Stable Diffusion, DALL-E, and MidJourney.

What you’ll learn:

  • Prompt patterns for specific outcomes
  • Combining tools (Python, APIs) with LLM prompts
  • Evaluation techniques for prompt success
  • Building smart workflows and agents

Here is the link to join this course —

Why Learn Prompt Engineering in 2025?

In order to show you why should learn prompt engineering let me show you both good and bad prompts and the output generated by them

Here’s the difference between good and bad prompts specifically for coding tasks:

Good Coding Prompt Example

Create a Python function that calculates the Fibonacci sequence up to n terms. The function should:
1. Accept a parameter 'n' (number of terms)
2. Include input validation to handle negative numbers and non-integers
3. Return the sequence as a list
4. Use recursion with memoization for efficiency
5. Include docstrings and comments explaining the implementation
6. Include 2-3 example test cases showing different inputs
My experience level is intermediate Python, so please explain any complex optimization techniques used.

Why it’s good:

  • Specific language: Clearly states Python
  • Well-defined task: Calculate Fibonacci sequence up to n terms
  • Technical requirements: Lists specific implementation details
  • Performance considerations: Mentions efficiency (recursion with memoization)
  • Documentation needs: Requests docstrings and comments
  • Testing approach: Asks for example test cases
  • Provides context: Mentions user’s experience level
  • Asks for explanations: Requests clarification of complex concepts

Bad Coding Prompt Example

Write code for Fibonacci.

Why it’s bad:

  • Ambiguous language: No programming language specified
  • Unclear requirements: Doesn’t specify what aspect of Fibonacci to implement
  • No performance guidelines: Doesn’t mention efficiency concerns
  • No error handling requirements: Doesn’t address edge cases
  • No documentation requirements: Doesn’t request comments or explanations
  • No context: Doesn’t mention user’s experience level or use case
  • No specific output format: Doesn’t specify return type or how to present results

Let me show you these functions to further illustrate the difference in the outputs you’d see.

Here is output from bad prompt first

and here is output from good prompt

You can see how the code from the good prompt includes comprehensive documentation, error handling, optimization through memoization, and thorough test cases — while the result from the bad prompt is minimal, lacks documentation, and provides only basic functionality.

That explains why its important for developers to learn aobut prompt engineering in 2025.

Prompt Engineering Cheat Sheet

And, here is the Prompt Engineering Cheat sheet I promised at the start. This shows key prompt engineering techniques and tips you can use to leverage LLM like ChatGPT or Claude better

Final Thoughts

Prompt Engineering is not just a technical skill — it’s a mindset. As LLMs become embedded in every aspect of software, business, education, and content creation, your ability to instruct and guide them effectively will determine your success.

Udemy’s wide range of affordable, up-to-date courses gives learners the chance to master this futuristic skill no matter their background.

Whether you’re a beginner exploring what ChatGPT can do or a developer building LLM-powered applications, one of these 7 courses will be the perfect next step in your learning journey.

By the way, if you want to join multiple course on Udemy, its may be worth getting a , which will give instant access of more than 11,000 top quality Udemy courses for just $30 a month. If you got a lot of time and want to save money, Udemy Personal Plan will be perfect for you.

Other AI, LLM, and Machine Learning resources you may like

Thanks a lot for reading this article so far, if you like these books then please share with your friends and colleagues. If you have any feedback or questions then please drop a note.

P.S. You can also join a course like to get some hands-on experience on building RAG based chatbot and learning LLM by watching. Don’t wait for your company to start using AI. Learn now, lead later.

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A humble place to learn Java and Programming better.

javinpaul
javinpaul

Written by javinpaul

I am Java programmer, blogger, working on Java, J2EE, UNIX, FIX Protocol. I share Java tips on and

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