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JavaScript Learning Path - 24 Hours

1. JavaScript Fundamentals (3 hours)

  • Variables and Data Types
    • var, let, const
    • Numbers, Strings, Booleans
    • null and undefined
    • Objects and Arrays
  • Basic Operators
  • Type Conversion
  • Control Flow
    • if/else statements
    • switch statements
    • loops (for, while, do-while)

2. Functions and Scope (3 hours)

  • Function Declaration vs Expression
  • Arrow Functions
  • Parameters and Arguments
  • Return Values
  • Scope and Closures
  • this keyword

Day 2 (6 hours)

3. Objects and Arrays Deep Dive (3 hours)

  • Object Methods and Properties
  • Array Methods
    • push, pop, shift, unshift
    • map, filter, reduce
    • forEach, find, some, every
  • Destructuring
  • Spread/Rest Operators

4. DOM Manipulation (3 hours)

  • Selecting Elements
  • Creating/Removing Elements
  • Event Handling
  • Event Bubbling and Delegation
  • DOM Traversal
  • Modifying Styles and Classes

Day 3 (6 hours)

5. Asynchronous JavaScript (3 hours)

  • Callbacks
  • Promises
  • Async/Await
  • fetch API
  • Error Handling
  • JSON

6. Modern JavaScript Features (3 hours)

  • ES6+ Features
  • Modules
  • Classes
  • Template Literals
  • Default Parameters
  • Optional Chaining
  • Nullish Coalescing

Day 4 (6 hours)

7. Practice Projects (4 hours)

  1. Todo List Application

    • CRUD operations
    • Local Storage
    • DOM manipulation
  2. Weather App

    • Working with APIs
    • Async operations
    • Error handling

8. Best Practices and Debug (2 hours)

  • Code Organization
  • Debugging Techniques
  • Performance Optimization
  • Common Pitfalls
  • Error Handling Patterns

Resources

  • MDN Web Docs
  • JavaScript.info
  • FreeCodeCamp
  • Codecademy

Practice Exercises

Each section should be followed by practical exercises to reinforce learning.

Project Ideas

  • Calculator
  • Form Validator
  • Quiz App
  • Notes App
  • Shopping Cart

Next Steps

  • Learn a Framework (React, Vue, or Angular)
  • Explore Node.js
  • Study Design Patterns
  • Practice Data Structures and Algorithms

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