Prompt Engineering Patterns for Developers โ€” WalkSelf

Prompt Engineering Patterns for Developers

Learn essential techniques like Chain-of-Thought and ReAct to generate reliable code using AI.

โฑ 38 min ๐Ÿ“š 9 lessons ๐ŸŽง Audio version

About this course

As AI tools become integral to software development, writing effective prompts is a crucial skill for any developer. Stop settling for unpredictable code outputs and learn how to guide AI to produce structured, reliable, and logical results. This text-based course introduces the core concepts of prompt engineering specifically tailored for coding tasks. You will explore how to structure your requests, manage context, and apply advanced cognitive patterns to improve AI-generated code. What you will learn: Understand foundational prompt engineering concepts, system prompts, and context management. Apply Chain-of-Thought reasoning to break down complex programming problems. Implement the ReAct pattern for dynamic problem-solving and logic generation. Practice reflection techniques to help AI self-correct and debug its own code snippets. Explore basic Retrieval-Augmented Generation (RAG) concepts to ground AI responses in your specific technical context. The course begins with essential terminology and the anatomy of a good prompt before moving into practical, text-based examples of advanced patterns. You will read through clear explanations and analyze code-focused prompt snippets to build your intuition. Designed for beginner developers and coding enthusiasts, this course requires no prior AI expertise. Start reading today to transform how you collaborate with AI in your development workflow.

What you'll get

  • ๐Ÿ“œ Certificate of completion
    Add it to your LinkedIn profile
  • ๐ŸŽง Audio version included
    Learn on the go โ€” no screen needed
  • โ™พ๏ธ Lifetime access
    Come back anytime, no expiry
  • ๐Ÿ“ฑ Phone or computer
    Works anywhere, any device
  • ๐Ÿ’ธ 14-day refund
    No questions asked
  • โšก Short & focused
    38 min of practical content

Reviews (3)

Finn Schulz CH
โ˜… 5 ยท 2026-03-14T01:24:43+00:00

Endlich verstehe ich, wie ich mit ReAct und Chain-of-Thought zuverlรคssigeren Code aus dem Modell herausbekomme.

Anna Kowalska PL Verified learner
โ˜… 5 ยท 2025-08-07T19:26:32+00:00

Wczeล›niej moje prompty do generowania kodu byล‚y doล›ฤ‡ przypadkowe i czฤ™sto musiaล‚em wszystko poprawiaฤ‡ rฤ™cznie. Ten kurs pokazaล‚ konkretne wzorce, zwล‚aszcza Chain-of-Thought, dziฤ™ki ktรณremu model rozbija problem na kroki i rzadziej siฤ™ myli. Sekcja o ReAct otworzyล‚a mi oczy na to, jak ล‚ฤ…czyฤ‡ rozumowanie z dziaล‚aniem, co ล›wietnie sprawdza siฤ™ przy bardziej zล‚oลผonych zadaniach. Wszystko podane praktycznie, z przykล‚adami, ktรณre od razu przetestowaล‚em u siebie. Jakoล›ฤ‡ generowanego kodu naprawdฤ™ poszล‚a w gรณrฤ™. Polecam kaลผdemu programiล›cie, ktรณry chce wycisnฤ…ฤ‡ wiฤ™cej z AI.

Isabella Wilson NZ Verified learner
โ˜… 4 ยท 2025-05-07T08:14:37+00:00

The Chain-of-Thought and ReAct sections genuinely improved my code-gen prompts, though I wanted one more worked example.

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Frequently asked

What do I need to take this course? +

Just a phone or computer with internet. No installs, no special hardware.

How do I pay? +

By card via Stripe. We donโ€™t store card details โ€” Stripe handles them securely.

Can I get a refund? +

Yes โ€” full refund within 14 days, no questions asked.

How long will I have access? +

Forever. Once you purchase, the course is yours to revisit anytime.

Will I get a certificate? +

Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.

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