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Mastering Prompt Engineering

It covers a wide range of topics, from prompt engineering theory and practical techniques to the latest application cases and security/ethical issues, providing practical assistance to LLM-based service developers, data scientists, and AI planners alike.

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73 learners

Level Intermediate

Course period Unlimited

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  • arigaram님의 프로필 이미지

    # Lecture 16. Mastering Prompt Engineering
    
    ## Notice on New Lesson Postings
    
    Hello, students! This course is scheduled to have **226** new lessons (across a total of 66 sections) posted sequentially. Since I am producing multiple courses simultaneously, I am proceeding by **alternating between various courses and posting a little at a time**, rather than uploading one entire course at once. Below are the posting principles and the schedule for each section of this course.
    
    > For your reference, the lessons being posted now are not entirely new content, but are part of the process of creating **revised editions (2nd or 3rd editions)** that reinforce existing lectures.
    
    ## Posting Principles
    
    - Currently, I am rotating through a total of 19 courses in order (circular method), posting one lesson per course alternately.
    - Postings are made on weekdays (Mon-Fri), with a total of 5 new lessons uploaded daily across all courses.
    - For this course, the next lesson will be posted each time its turn in the rotation comes around.
    - The posting speed may feel slow compared to other courses, but all courses are progressing together in the same manner.
    
    ## Posting Schedule by Section (Total 66 Sections)
    
    | Section | Number of Lessons | Start Date | End Date |
    |---|---|---|---|
    | Section 2. [Intro to Prompt Engineering] 2. Configuring LLM Usage Environment | 2 | 2026-07-06 | 2026-07-09 |
    | Section 3. [Intro to Prompt Engineering] 3. Basic Prompting | 4 | 2026-07-15 | 2026-07-31 |
    | Section 4. [Intro to Prompt Engineering] 4. Components of a Prompt | 2 | 2026-08-05 | 2026-08-11 |
    | Section 5. [Intro to Prompt Engineering] 5. General Tips for Prompt Design | 3 | 2026-08-17 | 2026-08-27 |
    | Section 6. [Intro to Prompt Engineering] 6. Prompt Examples | 3 | 2026-09-01 | 2026-09-11 |
    | Section 7. [Prompt Engineering Techniques] 1. Zero-Shot | 4 | 2026-09-17 | 2026-10-02 |
    | Section 8. [Prompt Engineering Techniques] 2. Few-Shot | 4 | 2026-10-08 | 2026-10-23 |
    | Section 9. [Prompt Engineering Techniques] 3. CoT (Chain of Thought) | 4 | 2026-10-29 | 2026-11-16 |
    | Section 10. [Prompt Engineering Techniques] 4. SC-CoT (Self-Consistency CoT) | 4 | 2026-11-19 | 2026-12-07 |
    | Section 11. [Prompt Engineering Techniques] 5. GKP (Generated Knowledge Prompting) | 4 | 2026-12-11 | 2026-12-28 |
    | Section 12. [Prompt Engineering Techniques] 6. Prompt Chaining | 3 | 2027-01-01 | 2027-01-12 |
    | Section 13. [Prompt Engineering Techniques] 7. ToT (Tree of Thoughts) | 5 | 2027-01-15 | 2027-02-03 |
    | Section 14. [Prompt Engineering Techniques] 8. RAG (Retrieval-Augmented Generation) | 6 | 2027-02-08 | 2027-03-02 |
    | Section 15. [Prompt Engineering Techniques] 9. ART (Automatic Reasoning and Tool-use) Theory | 9 | 2027-03-05 | 2027-04-06 |
    | Section 16. [Prompt Engineering Techniques] 10. AP (Active Prompting) | 4 | 2027-04-09 | 2027-04-22 |
    | Section 17. [Prompt Engineering Techniques] 11. APE (Automatic Prompt Engineer) | 3 | 2027-04-26 | 2027-05-04 |
    | Section 18. [Prompt Engineering Techniques] 12. DSP (Directional Stimulus Prompting) | 3 | 2027-05-07 | 2027-05-14 |
    | Section 19. [Prompt Engineering Techniques] 13. PAL (Program-Aided Language Models) | 3 | 2027-05-19 | 2027-05-27 |
    | Section 20. [Prompt Engineering Techniques] 14. ReAct | 5 | 2027-06-01 | 2027-06-15 |
    | Section 21. [Prompt Engineering Techniques] 15. MM-CoT (Multimodal CoT) | 4 | 2027-06-18 | 2027-06-29 |
    | Section 22. [Prompt Engineering Techniques] 16. GraphPrompt | 10 | 2027-07-02 | 2027-08-03 |
    | Section 23. [Applications] 1. Function Calling | 2 | 2027-08-05 | 2027-08-09 |
    | Section 24. [Applications] 2. Data Generation | 4 | 2027-08-11 | 2027-08-19 |
    | Section 25. [Applications] 3. Generating Synthetic Datasets for RAG | 2 | 2027-08-23 | 2027-08-25 |
    | Section 26. [Applications] 4. Dealing with Diversity in Generated Datasets | 3 | 2027-08-27 | 2027-09-02 |
    | Section 27. [Applications] 5. Code Generation | 4 | 2027-09-06 | 2027-09-14 |
    | Section 28. [Applications] 6. Case Study: Job Classification for New College Graduates | 3 | 2027-09-16 | 2027-09-22 |
    | Section 29. [Prompt Collection] 1. Classification | 2 | 2027-09-24 | 2027-09-28 |
    | Section 30. [Prompt Collection] 2. Coding | 2 | 2027-09-30 | 2027-10-04 |
    | Section 31. [Prompt Collection] 3. Creativity | 2 | 2027-10-06 | 2027-10-08 |
    | Section 32. [Prompt Collection] 4. Evaluation | 2 | 2027-10-12 | 2027-10-14 |
    | Section 33. [Prompt Collection] 5. Information Extraction | 2 | 2027-10-18 | 2027-10-20 |
    | Section 34. [Prompt Collection] 6. Image/Video Generation | 2 | 2027-10-22 | 2027-10-26 |
    | Section 35. [Prompt Collection] 7. Math Problem Solving | 2 | 2027-10-28 | 2027-11-01 |
    | Section 36. [Prompt Collection] 8. Q&A | 2 | 2027-11-03 | 2027-11-05 |
    | Section 37. [Prompt Collection] 9. Reasoning | 2 | 2027-11-09 | 2027-11-11 |
    | Section 38. [Prompt Collection] 10. Summarization | 2 | 2027-11-15 | 2027-11-17 |
    | Section 39. [Prompt Collection] 11. Truthfulness | 2 | 2027-11-19 | 2027-11-23 |
    | Section 40. [Prompt Collection] 12. Adversarial Prompting | 2 | 2027-11-25 | 2027-11-29 |
    | Section 41. [Major Models] 1. ChatGPT | 3 | 2027-12-01 | 2027-12-07 |
    | Section 42. [Major Models] 2. GPT-4 | 3 | 2027-12-09 | 2027-12-14 |
    | Section 43. [Major Models] 3. Gemini | 3 | 2027-12-16 | 2027-12-22 |
    | Section 44. [Major Models] 4. LLaMA | 3 | 2027-12-23 | 2027-12-29 |
    | Section 45. [Major Models] 5. Code Llama | 3 | 2027-12-30 | 2028-01-05 |
    | Section 46. [Major Models] 6. Flan | 4 | 2028-01-06 | 2028-01-13 |
    | Section 47. [Major Models] 7. Mistral 7B | 3 | 2028-01-17 | 2028-01-20 |
    | Section 48. [Major Models] 8. Mixtral | 3 | 2028-01-21 | 2028-01-27 |
    | Section 49. [Major Models] 9. Olmo | 3 | 2028-01-28 | 2028-02-02 |
    | Section 50. [Major Models] 10. Phi-2 | 3 | 2028-02-04 | 2028-02-09 |
    | Section 51. [Major Models] 11. Language Model Collection | 3 | 2028-02-11 | 2028-02-16 |
    | Section 52. [Risks and Misuse] 1. Defense Strategies Against Adversarial Prompting | 4 | 2028-02-18 | 2028-02-24 |
    | Section 53. [Risks and Misuse] 2. Factuality | 3 | 2028-02-28 | 2028-03-02 |
    | Section 54. [Risks and Misuse] 3. Bias | 4 | 2028-03-06 | 2028-03-10 |
    | Section 55. [Advanced] 1. System Prompt Design | 5 | 2028-03-14 | 2028-03-21 |
    | Section 56. [Advanced] 2. Structured Output | 3 | 2028-03-23 | 2028-03-28 |
    | Section 57. [Advanced] 3. Reasoning Models and Extended Thinking | 4 | 2028-03-29 | 2028-04-04 |
    | Section 58. [Advanced] 4. Multimodal Prompting in Practice | 3 | 2028-04-06 | 2028-04-10 |
    | Section 59. [Advanced] 5. Agents and Tool Use | 4 | 2028-04-12 | 2028-04-18 |
    | Section 60. [Advanced] 6. Prompt Evaluation and Optimization | 3 | 2028-04-19 | 2028-04-24 |
    | Section 61. [Advanced] 7. Prompt Caching and Cost Optimization | 3 | 2028-04-26 | 2028-04-28 |
    | Section 62. [Advanced] 8. Claude Prompting | 4 | 2028-05-02 | 2028-05-08 |
    | Section 63. [Prompt Collection] 13. Agent Workflows | 2 | 2028-05-09 | 2028-05-11 |
    | Section 64. [Prompt Collection] 14. Document Analysis | 2 | 2028-05-12 | 2028-05-16 |
    | Section 65. [Prompt Collection] 15. Data Analysis | 2 | 2028-05-17 | 2028-05-18 |
    | Section 66. [Advanced] Prompt Ceilings and Three-Layer Expansion - Context Engineering and Harness Engineering | 8 | 2028-05-22 | 2028-06-05 |
    | Section 67. [Practice] Beyond Prompts - Enhancing Prompt Techniques with Harnesses | 7 | 2028-06-06 | 2028-06-16 |
    
    ## Estimated Completion
    
    Based on the current pace, the estimated completion date for all postings of this course is **around June 2028**. (The actual schedule may be moved forward or delayed depending on production progress)
    
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  • arigaram님의 프로필 이미지

    At the request of our readers, we are issuing a 66% discount coupon for "Cognitive Load Management Techniques to Break Through the Limits of RAG Performance" (the 990,000 KRW course can be purchased for 330,000 KRW).

    For your information, this course is currently in the process of posting the 2nd edition, which is a revision of the 1st edition.

    In the case of the 2nd edition, all class materials have been posted, but the videos are still in the process of being uploaded.

    I post the 2nd edition videos frequently, but it will take a long time (at least several months) to post all of them.

    Please keep this in mind and carefully decide whether to use the coupon.

    The deadline is the 19th and there is a limited number of coupons available, so please hurry if you need one.

    You can download the coupon by entering the address below into your browser's search bar.

    https://inf.run/QowXG


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  • arigaram님의 프로필 이미지

    Hello.

    The era of AI writing code has arrived.

    However, the task of verifying the code written by AI and directing the path for improvement remains the responsibility of humans.

    Furthermore, it has become necessary to know how to utilize AI more extensively in both vertical and horizontal directions.

    The horizontal direction refers to a direction that encompasses everything from planning to deployment, and

    The vertical direction refers to a direction that can encompass various languages, various frameworks, and various methodologies.

    Therefore, a developer with a broad spectrum (that is, a complete spectrum in both vertical and horizontal directions)

    will be needed.

    However, the education system has not yet been able to keep up with this.

    That is why I have opened the "Structural Code Reading Bootcamp" using Claude Code.

    At https://code-reading-bootcamp.vercel.app/, you can develop the ability to read code written by both AI and humans, and

    You will be able to develop the ability to guide AI on how to improve code.

    It includes gamification elements, so you can have fun while tracking your skill improvements.

    It is free to use anytime without the need to log in.

    Although there are some shortcomings and parts where the questions have not yet been filled in,

    I introduce this with the hope that it will be helpful to you.

    I would appreciate it if you could use it lightly.

    February 10, 2026, Sincerely, Jinsu Park (Arigaram).

     

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$254.10