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AI Prompt Engineering

(AI-PROMPTENGG.AUJ1) / ISBN : 979-8-90059-984-7
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1

AI Foundations

  • Alan Turing and the Turing Test
  • Cybernetics
  • The Origin Story
  • Golden Age of AI
  • AI Winter
  • The Rise and Fall of Expert Systems
  • Neural Networks and Deep Learning
  • Technological Drivers of Modern AI
  • Structure of AI
  • Conclusion
  • Key Takeaways
2

Data

  • Data Basics
  • Types of Data
  • Big Data
  • Databases and Other Tools
  • Data Process
  • Ethics and Governance
  • More Data Terms and Concepts
  • Conclusion
  • Key Takeaways
3

Machine Learning

  • What Is Machine Learning?
  • Standard Deviation
  • The Normal Distribution
  • Bayes’ Theorem
  • Correlation
  • Feature Extraction
  • What Can You Do with Machine Learning?
  • The Machine Learning Process
  • Applying Algorithms
  • Common Types of Machine Learning Algorithms
  • Naïve Bayes Classifier (Supervised Learning/Classification)
  • K-Nearest Neighbor (Supervised Learning/Classification)
  • Linear Regression (Supervised Learning/Regression)
  • Decision Tree (Supervised Learning/Regression)
  • Ensemble Modelling (Supervised Learning/Regression)
  • K-Means Clustering (Unsupervised/Clustering)
  • Conclusion
  • Key Takeaways
4

Deep Learning

  • Difference Between Deep Learning and Machine Learning
  • So What Is Deep Learning Then?
  • The Brain and Deep Learning
  • Artificial Neural Networks (ANNs)
  • Backpropagation
  • The Various Neural Networks
  • Deep Learning Applications
  • Deep Learning Hardware
  • When to Use Deep Learning?
  • Drawbacks with Deep Learning
  • Conclusion
  • Key Takeaways
5

Robotic Process Automation (RPA)

  • What Is RPA?
  • Pros and Cons of RPA
  • What Can You Expect from RPA?
  • How to Implement RPA
  • RPA and AI
  • RPA in the Real World
  • Conclusion
  • Key Takeaways
6

Natural Language Processing (NLP)

  • The Challenges of NLP
  • Understanding How AI Translates Language
  • Voice Recognition
  • NLP in the Real World
  • Voice Commerce
  • Virtual Assistants
  • Chatbots
  • Future of NLP
  • Conclusion
  • Key Takeaways
7

Physical Robots

  • What Is a Robot?
  • Industrial and Commercial Robots
  • Robots in the Real World
  • Humanoid and Consumer Robots
  • The Three Laws of Robotics
  • Cybersecurity and Robots
  • Programming Robots for AI
  • The Future of Robots
  • Conclusion
  • Key Takeaways
8

Implementation of AI

  • Approaches to Implementing AI
  • The Steps for AI Implementation
  • Identify a Problem to Solve
  • Forming the Team
  • The Right Tools and Platforms
  • Deploy and Monitor the AI System
  • Conclusion
  • Key Takeaways
9

The Future of AI

  • Autonomous Cars
  • US vs. China
  • Technological Unemployment
  • The Weaponization of AI
  • Drug Discovery
  • Government
  • AGI (Artificial General Intelligence)
  • Social Good
  • Conclusion
  • Key Takeaways
10

Foundations of Prompts

  • The Role of Prompts in Interacting with ChatGPT
  • Anatomy of a Well-Constructed Prompt
  • Exploring Different Prompt Styles
  • Prompt Examples and Analysis
11

Crafting Contextual Prompts

  • Leveraging Context for More Relevant Responses
  • Harnessing Prior Chat Turns for Smooth Conversations
  • Incorporating The User’s Name and Details for Personalization
12

Asking Specific Questions

  • Techniques for Asking Clear and Direct Questions
  • Navigating Ambiguity: How to Get Precise Answers
  • Uncovering Hidden Information With Well-Formed Queries
13

Providing Constraints and Guidelines

  • Setting Constraints for Desired Output
  • Ensuring Ethical and Responsible Responses
  • Combining Constraints for Tailored Content
14

Creative Prompts for Diverse Content

  • Inspiring Creative Writing with Open-Ended Prompts
  • Generating Poetry, Stories, and Dialogues
  • Using Prompts to Generate Ideas and Concepts
  • Exploring Creativity Through Multimodal Prompts
15

Debugging and Iterating Prompts

  • Interpreting and Analyzing Model Responses
  • Identifying Misunderstandings and Errors
  • Strategies for Iterating and Improving Prompts
16

Advanced Prompt Engineering

  • Using Temperature, Top-P, and Max Tokens for Control
  • Incorporating Conditional Logic in Prompts
  • Dynamic Prompts for Interactive Experiences
17

Effective Use of Prompts And GPT-4 with Plugins

  • An Introduction to Plugins
  • Integrating Plugins for Enhanced AI Conversations
  • Benefits of Using Plugins
  • Popular Chatgpt/GPT-4 Plugins
18

Real-World Applications

  • Applying Prompt Engineering in Customer Support
  • Generating Content for Social Media and Marketing
  • Educational Use Cases: Teaching and Learning with ChatGPT
  • Business Applications
  • Technical and Engineering Applications
19

Future Trends and Ethical Considerations

  • The Evolving Landscape of AI-Generated Content
  • Addressing Bias and Fairness in Prompts and Responses
  • Ethical Considerations for Prompt Engineering
20

GPTs and GPT Application Builder

  • New Features Announced with GPTS
  • How to Build GPTS
  • Example 1-A GPT App for Coloring Pages
  • Example 2-A GPT App for Story Writers
  • Winding Down The ChatGPT Plugins
  • The Future of GPTS and GPT Builder
A

Appendix A: Miscellaneous Topics

  • Topics for Future Research and Development in AI
  • Teaching with AI
  • Multimodal GPT-4 with Voice and Image as Prompts
  • Common Pitfalls and Solutions

1

AI Foundations

  • Exploring AI History and Key Concepts
2

Data

  • Understanding and Managing Data Types Effectively
3

Machine Learning

  • Reviewing Machine Learning Concepts
4

Deep Learning

  • Exploring Deep Learning Concepts and Challenges
5

Robotic Process Automation (RPA)

  • Enhancing Operational Efficiency through Robotic Process Automation
6

Natural Language Processing (NLP)

  • Revising NLP Concepts
7

Physical Robots

  • Transforming Work with Robotics and AI
8

Implementation of AI

  • Deploying AI Systems
9

The Future of AI

  • Charting AI’s Transformation
10

Foundations of Prompts

  • Exploring Different Prompt Styles
11

Crafting Contextual Prompts

  • Crafting Contextual Prompts
12

Asking Specific Questions

  • Asking Clear and Direct Questions
13

Providing Constraints and Guidelines

  • Applying Constraints and Ethical Guidelines to Enhance ChatGPT Response Quality
14

Creative Prompts for Diverse Content

  • Exploring Creativity Through Multimodal Prompts
15

Debugging and Iterating Prompts

  • Implementing Strategies for Iterating and Improving Prompts
16

Advanced Prompt Engineering

  • Applying Advanced Techniques for Controlling ChatGPT
17

Effective Use of Prompts And GPT-4 with Plugins

  • Using Prompts and GPT-4 with Plugins Effectively
18

Real-World Applications

  • Exploring Real-World Applications of Prompt Engineering
19

Future Trends and Ethical Considerations

  • Exploring the Future of Prompt Engineering through Creative AI Applications
20

GPTs and GPT Application Builder

  • Exploring the Evolution of Custom GPTs and the Future of GPT Builder

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