AI Secrets of Prompt Engineering, Automation, Coding, Marketing , Advanced Topics Covered
What you will learn
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Introduction to Prompt Engineering , What is Prompt Engineering
AI Key Terms Prompt(Instructions given to AI) Model(AI System Processing the prompt) LLM(AI Trained on vast Data) Token(Smallest Unit of AI Text Processing)
How AI Models Work : Prediction , Learning & Limitations
Types of AI Prompts : Instructional , Conversational & Role-Based
Best Practices for Writing Effective Prompt : Be Specific , Give Context & Define Tone
Common Mistakes in Prompt Engineering : Vague Prompts (too General)= Weak Answers Too Much (AI gets confused break it up) Ignoring (Refine and Retry Prompts)
Testing and Refining Prompts : Test Versions (Small Tweaks Improve Answers) Add Details (AI Need Clear Instructions) Iterate(AI get Better with Refinement)
Chain-of-Thought Prompting : Explain Steps (Force AI to explain step by step) Problem-Solving (Better for logical tasks) Useful(Good for Math and Reasoning)
Zero-Shot (AI Guess Answer without Examples) versus Few-Shot Prompting (we give AI Examples for training , better and accurate Reponses)
Role-Playing & Context Setting : Make AI an Expert (Doctor ,Teacher, Developer). Context Improves Responses. Useful for business, learning and Problem solving
Multi-Step Prompts for Complex Tasks: Break big requests into smaller steps for better performance , AI is better with structured tasks
Meta-Prompting for Recursive Self Improvements : iteratively refine AI-generated prompts , applications in autonomous AI optimization
Neuro-symbolic Prompt-Integration (Symbolic Logic , Neural Networks , Hybrid Benefits)
Adversarial Prompt Defense Mechanisms : Detection , Classification , Neutralization , Adaption Phases
Hyperparameter Optimization for Prompts : Temperature Control , Top-k sampling , Top-p (Nucleus) Sampling, Repetition Penalties
Cross-Modal Prompt Engineering : Text Modality , Visual Modality , Code Modality , Audio Modality
Dynamic Context Window Management: Critical Info(Key context always retained) Recent Info(Near-term memory preserved) Background Info (Compressed for reference)
Integrating AI into Business & Productivity: integrate into daily routine , Streamline emails , reports & Scheduling , save time and boost productivity
Prompt Engineering for Coding & Automation : Code Generation(AI Writes & fix Code) Debugging(best with clear errors details) , (specify programming language)
Key Use Cases for Prompt Engineering Optimization (Workflow across Industries, Real-World applications AI driven prompts , efficiency )
AI Use Case: Research & Business Analysis : News Summarization , Academic Research , Business Reports
AI Use Case: Customer Support & Legal (AI Chatbots , Email Writing , Legal and Compliance)
AI Use Case: Human Resources & Software Development (HR & Recruitment , interview preparation (AI generate Questions)) , Coding & Debugging Writes and fix Code
AI Use Case : E-Commerce & data Processing
AI Use Case: Translation , Learning and Marketing
AI Use Case: Security and Automation
Ethical AI Prompting : Avoid Bias & Errors : Neutral Questions , Fast Check , Be Mindful
The Future of AI & Prompt Engineering (Smarter AI , Valuable Skills , AI Assistance)
How to Stay Ahead in AI & Prompt Engineering
Final Thoughts & Next Steps in Prompt Engineering
Final Challenge β Your AI Superpower!
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