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Master the Art of Prompt Engineering for Generative AI

Learn the Best Framework for Building Highly Effective Prompts for ChatGPT, Google Gemini and Microsoft Copilot

  1. Topics
  2. IT & Software
  3. Prompt Engineering

Master the Art of Prompt Engineering for Generative AI

InstructorIdan Gabrieli
Duration1h 4m
Students11.9K
Rating4.4 (4,113)
Sponsored
Price
$14.99
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Comidoc Analysis

A Structured Framework for Prompt Construction

Strengths

Structured Prompting Framework

The curriculum follows a clear sequence of six components—instruction, context, examples, persona, format, and tone—to build effective prompts.

Visualized Input-Output Differences

Lessons demonstrate how specific prompt changes impact the resulting AI output, providing a practical contrast between different inputs.

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The Complete AI Guide: Learn ChatGPT, Claude & Generative AIJulian Melanson4.5 (62.3K)41h 33m
AI A-Z [2026]: Agentic AI, Gen AI, Prompt Engineering and RLHadelin de Ponteves4.5 (50.3K)17h 22m
Generative AI for Digital Marketing: From Basics to ProAnton Voroniuk4.4 (4,232)77h 2m
ChatGPT & Generative AI - The Complete GuideAcademind by Maximilian Schwarzmüller4.6 (29.5K)21h 28m
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ChatGPTの使い方入門-生成AIビジネス活用 プロンプトエンジニアリングでより良い回答を得よう【GPT-5対応】中村 祐太 Yuta Nakamura4.2 (16.2K)4h 31m

Limitations

Limited Hands-on Application

The curriculum lacks explicit projects, quizzes, or dedicated hands-on activities to verify learning effectiveness.

Variable Conceptual Consistency

One signal suggests that the instructional flow may become disorganized or lose consistency after the initial chapters.

Best suited to

  • Beginners seeking a brief introduction to prompting
  • Non-technical learners looking for practical LLM interaction basics

Less suited to

  • Users requiring deep technical or coding-focused AI training
  • Learners seeking extensive hands-on practice or labs

Comidoc Score

6.5/10

Worth considering
Beginner-friendly

Comidoc verdict

The curriculum provides a structured six-step framework designed to teach the fundamental building blocks of prompt construction. This includes practical elements like persona adoption and task splitting, supported by clear examples showing how small changes alter AI responses.

However, the depth of the material is limited by a lack of hands-on exercises or technical projects for active application. Some signals also suggest that conceptual consistency may falter in later sections. This course is best suited for beginners or those needing a quick, high-level overview of prompting techniques.

Score breakdown

Curriculum depth
8.0

The curriculum covers essential methods like task splitting and knowledge generation, though signals suggest it lacks the depth required for more advanced or technical users.

Applied learning
5.0

While examples are used to illustrate concepts, the curriculum lacks formal projects, labs, or quizzes.

Clarity & experience
6.5

Instructional signals are generally positive regarding example clarity, though one signal notes potential issues with conceptual consistency and delivery.

Currency & reliability
5.0

The available evidence does not establish enough about current reliability to move this dimension away from neutral.

Audience fit
7.3

The curriculum aligns well with the declared beginner audience, though it may be too basic for those seeking technical or coding-centric applications.

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  • Generative AI Applications401
  • LLMs & ChatGPT Mastery114
  • Generative AI Basics97
  • Claude AI Mastery140