Chapter 1: Introduction to Modern JavaScript and TypeScript
- 1.1 Evolution of JavaScript
- 1.2 Core Concepts Refresher
- 1.3 Object-Oriented Programming in JavaScript
- 1.4 Introduction to Design Patterns
Chapter 2: Creational Design Patterns
- 2.1 Singleton Pattern
- 2.2 Factory Pattern
- 2.3 Builder Pattern
- 2.4 Prototype Pattern
Chapter 3: Structural Design Patterns
- 3.1 Adapter Pattern
- 3.2 Decorator Pattern
- 3.3 Facade Pattern
- 3.4 Proxy Pattern
Chapter 4: Behavioral Design Patterns
- 4.1 Observer Pattern
- 4.2 Strategy Pattern
- 4.3 Command Pattern
- 4.4 Iterator Pattern
Chapter 5: Structural Design Patterns (Continued)
- 5.1 Composite Pattern
- 5.2 Flyweight Pattern
- 5.3 Bridge Pattern
- 5.4 Module Pattern
Chapter 6: Behavioral Design Patterns (Continued)
- 6.1 Chain of Responsibility Pattern
- 6.2 Mediator Pattern
- 6.3 Memento Pattern
- 6.4 Visitor Pattern
Chapter 7: Advanced Asynchronous Patterns
- 7.1 Deep Dive into Promises
- 7.2 Advanced Async/Await Techniques
- 7.3 Advanced Patterns with Async Iterators and Generators
- 7.4 Cancellation and Abortable Operations
Chapter 8: Functional Design Patterns
- 8.1 Introduction to Functional Programming Concepts
- 8.2 Functional Design Patterns in JavaScript
- 8.3 Functional Programming in TypeScript
- 8.4 Functional Design Patterns Applied
Chapter 9: Reactive Programming Patterns
- 9.1 Introduction to Reactive Programming
- 9.2 Reactive Programming with RxJS
- 9.3 Reactive Patterns in User Interface Development
- 9.4 Advanced Reactive Patterns and Best Practices
Chapter 10: Metaprogramming and Reflection
- 10.1 Understanding Metaprogramming in JavaScript and TypeScript
- 10.2 Advanced Metaprogramming Techniques
- 10.3 Decorators and Metadata Reflection in TypeScript
- 10.4 Generics and Advanced Type Manipulation in TypeScript
Chapter 11: Patterns for Testing and Quality Assurance
- 11.1 Introduction to Testing in Modern JavaScript and TypeScript
- 11.2 Test-Driven Development (TDD) with Design Patterns
- 11.3 Mocking, Stubbing, and Test Doubles
- 11.4 Testing Design Patterns in Practice
Chapter 12: Performance Optimization Patterns
- 12.1 Understanding Performance Optimization
- 12.2 Code-Level Optimization Patterns
- 12.3 Application-Level Optimization Patterns
- 12.4 Scalability and Load Management Patterns
Chapter 13: Security Patterns in Modern Applications
- 13.1 Introduction to Security in Software Design
- 13.2 Authentication and Authorization Patterns
- 13.3 Input Validation and Data Sanitization Patterns
- 13.4 Secure Communication and Data Protection
Chapter 14: Microservices and Distributed Systems Patterns
- 14.1 Introduction to Microservices Architecture
- 14.2 Design Patterns for Microservices
- 14.3 Deployment and Operational Patterns
- 14.4 Data Management and Consistency
Chapter 15: Blockchain Design Patterns
- 15.1 Introduction to Blockchain Technology
- 15.2 Blockchain Architectural Patterns
- 15.3 Smart Contract Design Patterns
- 15.4 Security Patterns and Best Practices
Chapter 16: Artificial Intelligence Design Patterns
- 16.1 Introduction to AI Integration in Software Systems
- 16.2 Data Management and Preprocessing Patterns
- 16.3 Model Development and Deployment Patterns
- 16.4 Ethical AI Design Patterns
Appendix A: Interview Questions and Answers
- A.1 General Concepts
- A.2 Creational Design Patterns
  - A.2.1 Singleton Pattern
  - A.2.2 Factory Pattern
- A.3 Structural Design Patterns
  - A.3.1 Decorator Pattern
  - A.3.2 Proxy Pattern
- A.4 Behavioral Design Patterns
  - A.4.1 Observer Pattern
  - A.4.2 Strategy Pattern
- A.5 Advanced Topics
  - A.5.1 TypeScript Advanced Types and Generics
  - A.5.2 Asynchronous Programming Patterns
Appendix B: Glossary of Terms
Appendix C: Additional Resources
Appendix D: Code Samples and Exercises

16.2 Data Management and Preprocessing Patterns

In this section

Data Ingestion and Pipeline Pattern: Building Scalable AI Data Pipelines
Explore the Data Ingestion and Pipeline Pattern in AI systems, focusing on scalable and robust ETL processes for optimal model performance.
Feature Engineering and Transformation: Patterns for AI Model Enhancement
Explore the intricate patterns of feature engineering and transformation to enhance AI model accuracy. Learn about normalization, encoding, scaling, and automation techniques with practical examples in JavaScript and TypeScript.
Data Validation and Testing Pattern in AI Design
Explore the critical role of data validation and testing patterns in AI, ensuring model reliability and performance through robust data management practices.
Data Privacy and Compliance in AI Systems: Patterns and Practices
Explore comprehensive strategies and patterns for ensuring data privacy and compliance in AI systems, including techniques like anonymization, differential privacy, and federated learning, alongside practical implementations and ethical considerations.

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16.1 Introduction to AI Integration in Software Systems

16.3 Model Development and Deployment Patterns

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16.2 Data Management and Preprocessing Patterns

In this section