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Advanced Prompt Engineering for Everyone

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Advanced Prompt Engineering for Everyone

Instructor: Dr. Jules White

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47,836 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.8

781 reviews

Intermediate level

Recommended experience

Flexible schedule
9 hours to complete
Learn at your own pace
97%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.8

781 reviews

Intermediate level

Recommended experience

Flexible schedule
9 hours to complete
Learn at your own pace
97%
Most learners liked this course

Build your subject-matter expertise

This course is part of the ChatGPT: Master Free AI Tools to Supercharge Productivity Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

Unlock the full potential of generative AI and become a master of prompt engineering. Dive deeper into how you can use In-context Learning to build better and more reliable prompts. See how Retrieval Augmented Generation (RAG) works and what can go wrong that you can counteract with fact-checkable prompt formats. Overcome your struggles in getting the right output from generative AI models with template-based output formats to achieve precision in your interactions with AI models. Tap into powerful AI capabilities for tasks ranging from social media comment analysis to survey results interpretation and beyond. This course will empower you with the skills needed to build exceptional prompts, using simple techniques, such as preference-driven refinement, and become and expert in leveraging generative AI for productivity and creativity.

What You Will Learn: In-Context Learning: Understand how to provide context within prompts to guide AI models towards more accurate and relevant outputs. Learn techniques to embed contextual information that enhances the model’s understanding and performance. Retrieval Augmented Generation (RAG): Explore how to integrate retrieval systems with generative models to provide more precise and informed responses. This module covers the mechanisms to combine the strengths of both retrieval and generation. Template Pattern and Examples: Master the art of crafting template-based prompts to achieve consistent and desired outputs. Learn how to tell generative AI to fit its output into your format and overcome struggles with getting exactly what you want. Tapping Into AI Capabilities for Everyday Use: Delve into practical applications such as analyzing social media comments, interpreting survey results, and other everyday tasks where generative AI can make a significant impact. Gain hands-on experience with real-world examples. Building Great Prompts: Discover simple methods for constructing effective prompts. Learn how preference-driven refinement can elevate your prompt engineering skills, ensuring that outputs meet your exact needs and preferences.

What's included

7 videos1 reading1 assignment

7 videos•Total 64 minutes
  • Why Getting Generative AI to Write Like You is a Hard Prompt Engineering Task•7 minutes
  • Prompts, Instructions, & Writing•7 minutes
  • Iterative Refinement in a Conversation and Why It is Different•10 minutes
  • In-Context Learning, Writing, & Information Density•15 minutes
  • The Writing Persona Pattern•10 minutes
  • Example Selection is Critical for In-Context Learning•5 minutes
  • Preference-Driven Refinement of Prompts•11 minutes
1 reading•Total 1 minute
  • Learning More & Staying Connected•1 minute
1 assignment•Total 60 minutes
  • Build Your Writing Persona•60 minutes

What's included

5 videos1 assignment

5 videos•Total 31 minutes
  • Exploiting Generation•5 minutes
  • Five Ways to Solve the Problem•9 minutes
  • Generation Approaches•7 minutes
  • Generating Assessment Metrics•5 minutes
  • Automated Search•5 minutes
1 assignment•Total 75 minutes
  • Think More•75 minutes

What's included

8 videos1 assignment

8 videos•Total 63 minutes
  • The Five Components of a Prompt•10 minutes
  • Machine Learning for All•6 minutes
  • Performing Classification with Prompts•9 minutes
  • Clustering with Prompts•5 minutes
  • Prediction with Prompts•8 minutes
  • Recommendation with Prompts•4 minutes
  • Training Models with Prompts: In-Context Learning•13 minutes
  • How Many Examples and Which Examples Should Your Prompt Use?•8 minutes
1 assignment•Total 90 minutes
  • AI, Training, & Prompts•90 minutes

What's included

5 videos1 assignment

5 videos•Total 34 minutes
  • Template Pattern•8 minutes
  • What is Markdown•6 minutes
  • Self-consistency, Fact Checking, & Referencing Footnotes•10 minutes
  • More Advanced Markdown Templates•7 minutes
  • Escape Valves in Prompts•4 minutes
1 assignment•Total 60 minutes
  • Building a Reporting Prompt•60 minutes

What's included

5 videos

5 videos•Total 42 minutes
  • Overview of RAG•8 minutes
  • Retrieval Approaches: Search, Databases, & Embeddings•14 minutes
  • The Important of Prompt Engineering in Augmentation•7 minutes
  • Issues with Retrieval: Finding the Right Thing, Chunk Size, & Noise•10 minutes
  • Thanks•3 minutes

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Instructor

Instructor ratings
4.7 (381 ratings)

Top Instructor

Vanderbilt University
52 Courses•1,199,972 learners

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Learner reviews

  • 5 stars

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  • 4 stars

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  • 3 stars

    2.29%

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Showing 3 of 781

CJ
·

Reviewed on Dec 15, 2025

The delivery of this course was clear, and the assignments allowed for a direct application of the material. Thank you for sharing your expertise, Professor Jules White.

MS
·

Reviewed on Jul 2, 2025

This was such an interesting and useful course! Really enjoyed it and look forward to doing more courses by Jules.

DV
·

Reviewed on Sep 5, 2024

Jules has so much insight into prompt engineering and why what he is teaching is important. I really appreciate his approach to teaching.

Frequently asked questions

You'll learn how to write prompts that give you more reliable, structured, and useful AI outputs. It starts with writing and in-context learning, then builds into stronger control through template-based formatting and retrieval-augmented generation (RAG). Along the way, you'll apply the ideas to tasks like creating a writing persona or turning source information into a more structured analysis.

Some familiarity with generative AI will help, because this is an intermediate course rather than a from-scratch introduction. It moves fairly quickly into topics like in-context learning, output formatting, and retrieval instead of spending much time on basic prompting. If you've already experimented with AI tools and want better control over the results, the pace should feel reasonable.

It's a better fit for learners who already know the basics of using generative AI and want to get more precise with prompts. The teaching is clear, but the course assumes you're ready to think about examples, tone, structured outputs, and how retrieved information affects answers. If you're completely new to prompting, a more introductory course may be an easier starting point.

The course takes about 9 hours in total. That's short enough to finish in a few focused study sessions, while still leaving room to work through the examples and assignments. The workload includes lessons, a reading, and graded practice assignments.

Yes, there is hands-on work, though it's more assignment-based than project-heavy. You'll create prompts for tasks like building a writing persona, proposing multiple pathways toward a goal, and generating a report with headers, tables, and footnotes from source data. The practice is guided, so you apply each technique as you learn it instead of being left with a large open-ended project.

You'll spend most of the course learning how to make prompts more reliable, reusable, and easier to evaluate. That includes in-context learning, retrieval-augmented generation (RAG), and structured prompt formats that help control how answers are written. By the end, you should have a clearer sense of how to design prompts for writing, analysis, and everyday decision support tasks.

After finishing, you should be able to write prompts that produce clearer, more structured, and more trustworthy AI outputs. You'll know how to refine a prompt, use examples to guide style or behavior, and set up formats that make responses easier to check. For example, you could build a reusable prompt to analyze survey responses or generate a report that ties claims back to source facts.

It's more concept-first than project-heavy, with guided practice built in. Most of the course explains why prompt choices change the output, then asks you to apply those ideas in focused assignments rather than large open-ended builds.

This course is a strong choice if you want prompt engineering taught as a repeatable working method, not just a list of prompt tips. It connects writing style, structured outputs, and RAG, and the assignments ask you to build reusable prompts for real tasks like reports and response analysis. If you already know the basics and want a short intermediate course focused on control and reliability, it's a very good fit.

Financial aid available,