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Prompt Engineering: Complete Guide

Master prompt engineering perfectly, an essential skill for developers in the AI era.

(3.7) 수강평 6개

강의소개.상단개요.수강생.short

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prompt engineering
prompt engineering
LLM
LLM
Python
Python
prompt engineering
prompt engineering
LLM
LLM
Python
Python

강의상세_배울수있는것_타이틀

  • Effective Prompt Engineering Techniques

  • Strategies for Increasing Prompt Evaluation Accuracy

  • Large Language Model (LLM) Mechanism Mastery

  • How to Use Advanced Prompt Techniques

Can you survive as a developer in the rapidly evolving AI era? 🧐

Today's development landscape is rapidly evolving beyond simple web development and into AI technology . Are you prepared? To avoid falling behind in this changing environment, we need to consider what truly critical capabilities are essential for AI development. " Prompt design skills " are the cornerstone.

You think prompt design should be left to prompt engineers? Prompt design skills are no longer a specialized skill reserved for a select few . Back when information retrieval technology was first emerging, the difficulty of searching gave rise to the profession of "information retrieval specialist." Does that profession still exist today? No.

Going forward, developers will need to design prompts as if they were writing code . Prompt design is now a fundamental language-level skill that everyone should master, much like learning Java . This course will systematically teach you everything from the basic concepts of LLM to advanced prompt design techniques . By mastering the essential skills for the AI era, you will be able to grow into a developer who is one step ahead. I believe this course will serve as a solid foundation for your career advancement.

Why I Created This Course

  • Since the birth of the web, countless developers have jumped into web development, creating a new technological ecosystem. Now, with the advent of large-scale language models (LLMs), another paradigm shift is dawning. In the coming AI era, application development will become as natural as web development, and the key competency leading this trend is prompt design.

  • I've learned this from developing AI applications. It's not enough to simply ask a model questions and receive results; you need the "fundamentals" to derive the desired answers . These fundamentals are essential skills for future developers . Just as learning languages like Java or Python is essential, the ability to design prompts is now becoming an essential skill.

  • In this context, I designed this course as a preparatory step for the coming era. Over the past four months, I've dedicated countless hours to this course. I've spent countless hours on my laptop, weekdays and weekends alike, revisiting drafts, reviewing papers, brainstorming better delivery methods, creating hands-on examples, and refining the concepts. This course, born from this process, embodies both my own personal insights and the core principles I believe future developers should grasp. I hope this course will serve as a solid foundation for developers entering the AI era.


Lecture Features

📌 It is structured so that you can learn everything from the basic concepts of what LLM is to advanced prompting techniques , and expand your skills step by step based on a solid foundation.

📌 We provide practical know-how that can be applied immediately in actual service environments through Anthropic API integration and model parameter setting methods .

📌 By learning prompt design methods and evaluation techniques , you can gain the ability to accurately elicit desired responses, thereby maximizing the efficiency of model utilization.

📌 You can learn strategies to maximize the potential of models by solving complex problems step by step through advanced techniques such as In-Context Learning, Decomposition, Self-Criticism, and Ensembling .

📌 Flow Engineering and Auto Prompt Engineering help you optimize the process of designing, managing, and automating prompts, building workflows that maximize development productivity and maintain consistent quality.

📌 Through advanced prompting techniques analyzed and applied in approximately 60 recent papers , this course presents practical strategies based on cutting-edge research results.

I recommend this to these people

I want to prepare for the AI era.

Developers who want to learn techniques to effectively handle LLM and Prompt design and produce results that can lead to business value.

I want to improve the quality of LLM-based services.
Developers who want to maximize model performance and achieve better results through various prompting strategies.

I want to quickly validate new features and ideas.

Entrepreneurs who want to quickly test early-stage services or prototypes with LLM and efficiently select promising ideas.

After class

  • Beyond simply calling LLM, you'll gain the ability to design sophisticated prompts to elicit the exact answers you want.

  • Understanding the different LLM models will help you choose the optimal prompting strategy for your situation and goals.

  • By mastering automated prompt design and conversation flow management techniques, you will be able to achieve efficient and consistent results even in complex service environments.

  • Advanced techniques such as In-Context Learning, Self-Criticism, and Ensembling can help you overcome model limitations and elevate service quality to the next level.

  • By acquiring "prompt design skills" for the AI era, you'll secure a solid foundation for becoming a competitive developer in the market.

Learn about these things.

Basic LLM Concepts: What is LLM? Exploring the Transformer Architecture and Various Model Types

Did you think LLM was just a simple "text predictor"? Expand your understanding of LLM, from analyzing Transformer architectures to exploring various model types. Only by properly understanding LLM can you effectively utilize it.

Anthropic API Fundamentals: Talking to LLMs and Handling Model Parameters

It doesn't end with simply "calling an API." We'll explore how to connect to the Anthropic API and adjust various parameters to achieve optimal model performance and response quality. Now, you can tailor your model to your needs.

Prompt Engineering: Designing the Right 'Instructions'

Telling a model to "just figure it out" is unlikely to yield the desired answer. Learn the skills to elicit the desired answer from a model through clear prompt design methods and evaluation techniques. These are the fundamental skills every developer will need in the future.

Advanced Prompt Techniques: In-Context Learning, Self Criticism, Ensembling, etc.

We cover advanced techniques that enable models to go beyond simply providing answers, but instead think and evaluate independently to produce more complete results. Learn strategies for leveraging models at a more advanced level, such as expanding context with examples, solving complex problems step-by-step, and combining various prompts.

Things to note before taking the course

Practice environment

  • The lecture is based on MacOS.

  • The Code Editor uses a Cursor.

  • In this exercise, we use Anthropic's Claude model. Throughout the course, calling the Claude model's API costs approximately $10. This is covered in detail in the course.

Learning Materials

  • I will share the files used in the lecture.

  • I am sharing all the links to the papers I referenced while creating the lecture.

Player knowledge

  • Basic Python Grammar

Note

  • My lecture is suitable for LLM holders and those seeking practical application of prompt design skills . If you want to focus more on background knowledge and fundamental concepts related to the AI era, as well as the fundamental theory of prompt engineering, I recommend the book "The Best Prompt Engineering Course" over my lecture. (This recommendation is not sponsored.)


강의소개.콘텐츠.추천문구

학습 대상은 누구일까요?

  • Aspiring AI engineer

  • A person not wanting to fall behind in AI development.

  • Person who wants to apply AI projects utilizing LLM in practice

선수 지식, 필요할까요?

  • Python basics (loops, conditionals, etc.)

강의소개.지공자소개

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3

강의_other

Hello.

As both a developer and an educator, I strive to create trustworthy courses.

When creating lectures, I strive to provide high-density content that delivers essential knowledge and skills concisely, without any unnecessary filler.

I only create courses in fields I am interested in and areas I believe are truly meaningful; I do not make courses that anyone else could easily create.

I also write useful posts on Careerly.

- (Former) Software Engineer at Kakao Enterprise

- (Former) Kakao Ground X Software Engineer

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  • gooofy님의 프로필 이미지
    gooofy

    수강평 1

    평균 평점 5.0

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    5

    100% 수강 후 작성

    I took the course because I needed to tune the prompt in detail after using LLM only as a basic tool. It was a lecture that allowed me to understand various methodologies for writing and improving prompts. I liked that it started with the structure and features of LLM and then explained each theory in detail! It was a satisfying lecture that covered not just obvious and simple content, but also how to properly use LLM to improve the quality of the results. Thank you.

    • whseo5586님의 프로필 이미지
      whseo5586

      수강평 2

      평균 평점 5.0

      5

      32% 수강 후 작성

      • lek11258473님의 프로필 이미지
        lek11258473

        수강평 1

        평균 평점 5.0

        5

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        • kimyr5904님의 프로필 이미지
          kimyr5904

          수강평 2

          평균 평점 5.0

          5

          32% 수강 후 작성

          • endless님의 프로필 이미지
            endless

            수강평 3

            평균 평점 3.7

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            1

            50% 수강 후 작성

            During the coding sections of the lectures, no code is provided and there's no explanation - just the instructor coding alone with fast-forwarded recording, making it impossible to follow along with the coding, and it moves too quickly to time the pauses properly. Adjusting the video speed every time is also cumbersome. The provided lecture materials are mostly just a few summary lines about the lecture, and many of these are duplicate pages. It seems like one final page would suffice, but everything that's added step-by-step as explained in the video is included as-is. When important conceptual terms are in English, the pronunciation is hard to understand, but they're not written in the lecture materials, and most of it proceeds with audio recording, making it difficult to take the course. They briefly write 4-5 lines on one PPT page, explain only verbally, and move on... I'm still early in the course, but I hope improvements can be made later on.

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