The Prompt Engineering Grandmaster Journey is a comprehensive professional learning program designed to provide end-to-end mastery of prompt engineering, reasoning architectures, automation, and applied LLM system design.
It consolidates the structure and rigor of a university-style curriculum with the flexibility of a self-paced mastery path, covering all levels—from foundational theory to research-grade application.
This repository contains all materials for the course, including detailed syllabi, learning paths, overviews, and project documentation.
- Develop a deep understanding of large language models (LLMs) and how they interpret and respond to prompts.
- Build technical skill in zero-shot, few-shot, and chain-of-thought prompting.
- Design advanced architectures including ReAct, Tree-of-Thoughts, and multi-agent reasoning systems.
- Automate and evaluate prompt workflows using APIs, LangChain, and LlamaIndex.
- Integrate multimodal models (text, image, audio, video) into creative and professional pipelines.
- Uphold ethical, responsible, and secure prompt engineering practices.
- Produce deployable prompt-based applications and research-quality systems.
Prompt-Engineering-Grandmaster-Journey/ │ ├── README.md → High-level overview, badges, quick links, license note ├── LICENSE → CC BY-NC-ND 4.0 (non-commercial, no-fork) ├── OVERVIEW.md → Detailed description of the program vision ├── learning_path.md → Combined university + mastery roadmap ├── table_of_contents.md → Complete syllabus and breakdown │ │ ├── 00_Admin_and_General/ → Repository-wide management and info │ ├── README.md → Welcome page + repository map │ ├── folder_guide.md → How folders are organized │ ├── update_log.md → Change log and version notes │ └── credits_and_acknowledgments.md │ │ ├── 01_Structured_Academic_Curriculum/ → (Weeks 1–12) Foundational academic pathway │ ├── 01_Foundations_of_LLMs_and_Prompting/ │ │ ├── README.md → Chapter content, subtopics, and project brief │ │ ├── notes.md → Instructor notes, visuals │ │ ├── diagrams/ → Model diagrams, architecture flows │ │ └── project_link.md → Link to Project_01 file │ ├── 02_Fundamentals_of_Prompt_Design/ │ │ ├── README.md │ │ └── examples/ │ ├── 03_Zero_Shot_and_Few_Shot_Prompting/ │ │ ├── README.md │ │ └── demo_prompts/ │ ├── 04_Chain_of_Thought_and_Reasoning/ │ │ ├── README.md │ │ └── stepwise_examples/ │ ├── 05_Prompt_Patterns_and_Frameworks/ │ │ ├── README.md │ │ └── frameworks/ │ ├── 06_Prompt_Debugging_and_Optimization/ │ │ ├── README.md │ │ └── debug_logs/ │ ├── 07_Advanced_Prompt_Architectures/ │ │ ├── README.md │ │ └── architecture_notes/ │ ├── 08_Prompt_Programming_for_Developers/ │ │ ├── README.md │ │ ├── code_samples/ │ │ └── api_integration.md │ ├── 09_Applied_Prompting_Across_Domains/ │ │ ├── README.md │ │ └── case_studies/ │ ├── 10_Automation_and_Prompt_Systems/ │ │ ├── README.md │ │ └── templates/ │ ├── 11_Ethics_and_Responsible_Prompting/ │ │ ├── README.md │ │ └── guidelines/ │ └── 12_Capstone_I_Specialized_AI_Assistant/ │ ├── README.md │ ├── architecture_diagram.png │ └── evaluation_criteria.md │ | ├── 02_Self_Paced_Mastery_Track/ → Deep research and experimentation phase │ ├── 13_Deep_Concept_Mastery_and_Research/ │ │ ├── README.md │ │ └── papers/ │ ├── 14_Workflow_Automation_and_Tooling/ │ │ ├── README.md │ │ └── scripts/ │ ├── 15_Multimodal_and_Generative_Prompting/ │ │ ├── README.md │ │ ├── image_prompts/ │ │ ├── video_prompts/ │ │ └── creative_workflows/ │ ├── 16_Multi_Agent_and_Systemic_Design/ │ │ ├── README.md │ │ └── agent_frameworks/ │ ├── 17_Professional_Practice_and_Monetization/ │ │ ├── README.md │ │ └── portfolio_samples/ │ └── 18_Capstone_II_Master_Engineer_Challenge/ │ ├── README.md │ ├── deployment_guide.md │ └── showcase/ │ │ ├── 03_Projects_and_Labs/ → All 18 project files with deliverables │ ├── Project_Index.md │ ├── Project_01_Foundational_Prompt_Analysis.md │ ├── Project_02_Persona_Prompt_System.md │ ├── Project_03_Few_Shot_Text_Classifier.md │ ├── Project_04_Analytical_Reasoning_Assistant.md │ ├── Project_05_Multi_Persona_Dialogue_Agent.md │ ├── Project_06_Prompt_Debugging_Journal.md │ ├── Project_07_Self_Reflective_Reasoning_Agent.md │ ├── Project_08_Domain_Specific_AI_Utility.md │ ├── Project_09_Applied_Multi_Domain_Prompt_Suite.md │ ├── Project_10_Prompt_Operating_System.md │ ├── Project_11_Ethical_Prompt_Policy.md │ ├── Project_12_Specialized_AI_Assistant.md │ ├── Project_13_Empirical_Prompt_Research_Study.md │ ├── Project_14_Automated_Prompt_Testing_Framework.md │ ├── Project_15_Multimodal_Creative_System.md │ ├── Project_16_Collaborative_AI_Team.md │ ├── Project_17_Prompt_Engineering_Portfolio.md │ └── Project_18_Master_Engineer_AI_Solution.md │ | ├── 04_Assessments_and_Progress/ → Evaluation and tracking │ ├── README.md │ ├── lab_exercises.md │ ├── evaluation_rubrics.md │ ├── progress_tracker_template.xlsx │ ├── peer_review_checklist.md │ └── certification_criteria.md │ │ ├── 05_Resources_and_References/ → Reference materials and libraries │ ├── recommended_readings.md │ ├── research_papers_list.md │ ├── prompt_pattern_library.md │ ├── tools_and_apis.md │ ├── data_samples/ │ │ ├── classification_examples.csv │ │ └── prompt_inputs.json │ ├── visual_assets/ │ │ ├── LLM_architecture.png │ │ └── ReAct_flow_diagram.png │ └── glossary_of_terms.md │ | ├── 06_Appendices_and_Templates/ → Support documents │ ├── appendix_a_prompt_patterns.md │ ├── appendix_b_scoring_templates.md │ ├── appendix_c_reading_list.md │ ├── appendix_d_tools_resources.md │ └── appendix_e_glossary.md │ │ ├── 07_Docs_and_Publishing/ → Documentation setup for GitHub Pages │ ├── index.md │ ├── site_navigation.md │ ├── style_guide.md │ ├── changelog.md │ ├── _config.yml → Jekyll (GitHub Pages config) │ ├── mkdocs.yml → (Optional, MkDocs) │ └── branding_assets/ │ ├── favicon.ico │ ├── logo.png │ └── banner.png │ │ ├── 08_Org_And_Automation/ → GitHub workflows and internal scripts │ ├── .github/ │ │ ├── workflows/ │ │ │ ├── pages_build.yml │ │ │ ├── toc_updater.yml │ │ │ └── spell_check.yml │ │ └── ISSUE_TEMPLATE.md │ ├── scripts/ │ │ ├── generate_structure.sh → Creates all directories automatically │ │ └── auto_toc.py → Rebuilds ToC from folder names │ └── requirements.txt → For automation scripts │ │ └── 09_Assets_and_Media/ → Logos, certificates, graphics ├── logos/ │ ├── shimu-labs-logo.png │ └── course-banner.png ├── diagrams/ │ ├── prompting_frameworks.png │ └── CoT_vs_ReAct_comparison.png ├── certificates/ │ ├── certificate_template.pdf │ └── digital_badge.png └── misc/ └── icons.svg
A structured progression through 12 chapters:
- Foundations of LLMs and Prompting
- Fundamentals of Prompt Design
- Zero-Shot and Few-Shot Techniques
- Chain-of-Thought Reasoning
- Prompt Patterns and Behavioral Frameworks
- Prompt Debugging and Optimization
- Advanced Architectures (ReAct, ToT, Reflection)
- Prompt Programming for Developers
- Applied Prompting Across Domains
- Automation and Prompt Systems
- Ethics, Bias, and Responsible Prompting
- Capstone I – Specialized AI Assistant
Extended independent study covering:
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Deep Concept Mastery and Research Integration
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Prompt Programming and Workflow Automation
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Multimodal and Generative Prompt Engineering
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Multi-Agent and Systemic Prompt Design
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Professional Practice and Monetization
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Capstone II – The Master Engineer Challenge
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Clone the repository
git clone https://github.com/<your-username>/Prompt-Engineering-Grandmaster-Journey.git
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Explore materials
- Begin with
01_Course_Overview/README.mdfor context. - Follow the
03_Learning_Path/to progress sequentially or self-pace by interest.
- Begin with
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Complete projects
- Each chapter includes a practical project; deliverables are detailed in
05_Projects/.
- Each chapter includes a practical project; deliverables are detailed in
- LLMs: GPT-5 (or equivalent), Claude, Gemini, Mistral
- Frameworks: LangChain, LlamaIndex, DSPy
- Languages: Python, JavaScript
- Creative Tools: Midjourney, DALL·E, Runway, Veo
- Version Control: Git, GitHub Projects for progress tracking
Developed and curated by [Your Name], based on advanced academic and professional standards in prompt engineering and AI systems design.
This repository consolidates key learning concepts, project frameworks, and reference materials for the 2025 cohort of learners, researchers, and professionals in generative AI.
This documentation is licensed under the CC BY-NC-ND 4.0. See the LICENSE file for details.
You may optionally include:
- A “Progress Tracker.md” file for learners to log completed modules.
- A “Contributing.md” file if collaborators will expand or adapt the content.
- A “Changelog.md” file to record future updates to course content.
The main README serves as the index and orientation document. It should:
- Introduce the program clearly.
- Reference the other README files that contain detailed material.
- Help new visitors understand the course structure, purpose, and navigation immediately.
This repository is made publicly visible for educational and reference purposes only.
You are welcome to:
- View, read, and reference the materials.
- Star or share the repository link.
You are not permitted to:
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