Prompt Engineering Full Course
At a glance
- Length
- 38 min
- Channel
- Tech With Tim
- Video from
- Mar 2026
- Rating
- ⭐⭐ Great video · 2/2
- Best for
- Developers and AI practitioners building with language models
What Prompt Engineering Covers in This Full Course
This comprehensive course from Tech With Tim breaks down prompt engineering from fundamentals to advanced techniques. The video walks through what prompt engineering is, why it matters when working with large language models, and practical methods to improve your results faster. The material spans foundational concepts all the way to specialized strategies for extracting maximum value from AI systems.
The course positions itself as a complete learning path for anyone wanting to understand how to communicate effectively with AI models. Rather than treating prompting as intuitive guesswork, the video structures it as a learnable skill with measurable techniques and identifiable mistakes to avoid.
Key Moments
Key Techniques and Methods Covered
- The distinction between steering and commanding — understanding how to guide rather than force AI responses
- Few-shot prompting — showing examples within your prompt to shape model behavior
- Chain of thought — encouraging step-by-step reasoning instead of jumping to conclusions
- Structured output formatting — requesting responses in specific formats like JSON or markdown
- Constraints and negatives — defining what the model should avoid alongside what it should do
- Iterative refinement — improving results through repeated adjustment and testing

Who Should Watch This Prompt Engineering Tutorial
This course suits developers, AI practitioners, and anyone building systems that depend on large language models. If you're currently using AI tools but feel like you're not getting consistent, high-quality results, this systematizes the trial-and-error approach into concrete strategies.
The course also appeals to technical professionals exploring monetization angles with AI or seeking to improve their productivity workflows. The pacing and depth suggest it works both as a reference guide and a sequential learning experience, making it useful whether you're completely new to prompting or refining techniques you already use informally.
Common Questions About This Prompt Engineering Course
What does the video mean by "how LLMs think"?
The video includes a section examining the internal logic of how large language models process and generate responses, helping you understand why certain prompting strategies work better than others.
Is this course suitable for beginners with no AI experience?
Yes. The video starts with foundational definitions and builds progressively, beginning with an explanation of what prompt engineering is before moving into specific techniques and advanced parameters.
What are "advanced techniques and parameters" mentioned in the course?
The video covers specialized methods and model settings that go beyond basic prompting, designed for users who want finer control over AI output and deeper optimization of their workflows.
Does the course include practical examples or templates?
The video provides a markdown file resource available through the channel, which gives you structured material to reference while applying the techniques discussed.
How does "interview style prompting" differ from standard prompts?
The video includes a dedicated segment on interview-style prompting as a distinct technique, suggesting it's a specialized method for eliciting certain types of responses from language models.

Key Terms
- Prompt engineering
- The practice of crafting and refining inputs to language models to consistently get better, more useful results.
- Few-shot prompting
- Providing examples within your prompt to teach the model what kind of output you want.
- Chain of thought
- Asking a model to show its reasoning step-by-step rather than jumping directly to an answer.
- LLM
- Large language model—an AI system trained on text data to generate human-like responses.
- Structured output
- Requesting responses in a specific format, such as JSON or bullet points, rather than free-form text.
Sources: Prompt engineering · Few-shot prompting · Chain of thought · LLM · Structured output — definitions cross-referenced with Wikipedia
Video by Tech With Tim on YouTube. If you enjoyed it, please subscribe to their channel and show your support for the great video.
Description
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In this video, you'll learn everything you need to know about prompt engineering. I'll explain what it is, why it's important, how to do it faster. The top techniques and methods and advanced strategies to get the most out of loops.
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🎞 Video Resources 🎞
Get the markdown file in this video: https://newsletter.techwithtim.net/prompting
⏳ Timestamps ⏳
00:00 | Intro
01:44 | What is Prompt Engineering
04:07 | How to Prompt Faster
07:05 | How LLMs "Think"
10:40 | Steering vs Commanding
11:53 | Be Specific & Set the Scene
14:32 | Few-Shot Prompting
18:10 | Chain of Thought
20:05 | Structured Output
22:04 | Constraints & Negatives
24:19 | Iterative Refinement
25:22 | Interview Style Prompting
29:13 | Advanced Techniques & Parameters
35:04 | Common Mistakes
Hashtags
#LLMs #AiPrompts #SoftwareEngineer
UAE Media License Number: 3635141
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