Unit 2: Introduction to Programming Concepts and Paradigms

1. Overview of Programming

• Definition and purpose of programming
• Importance of programming in technology and problem-solving
• Basic principles of programming languages
  • Syntax and semantics
  • Compilation vs. interpretation

2. Programming Paradigms

• Procedural Programming
  • Definition and characteristics
  • Advantages and limitations
• Object-Oriented Programming (OOP)
  • Key concepts overview
  • Advantages and limitations
• Functional Programming
  • Core features and concepts
  • Advantages and limitations
• Comparison of paradigms and use cases

3. Variables and Data Types

• Concept of variables
• Common data types
  • Integers
  • Floating-point numbers
  • Strings
  • Boolean
• Variable declaration and initialization
• Scope and lifetime of variables

4. Control Structures

• Conditional statements
  • if-else constructs
  • switch-case statements
• Looping constructs
  • for loops
  • while loops
  • do-while loops
• Nested control structures

5. Functions and Methods

• Definition and purpose of functions/methods
• Syntax for defining functions
• Function parameters and arguments
• Return values
• Scope of variables inside functions
• Method overloading (brief introduction)

6. Arrays and Lists

• Introduction to arrays
  • Declaration and initialization
  • Indexing and accessing elements
• Lists as dynamic data structures
  • Adding/appending elements
  • Iterating through lists
• Common operations and use cases

7. Object-Oriented Programming (OOP) Concepts

• Classes and objects
• Encapsulation
  • Access modifiers
• Inheritance
• Polymorphism
• Benefits of OOP: reusability and modularity

8. Exception Handling

• Concept of errors and exceptions
• try-catch blocks
• Throwing and catching exceptions
• Finally block and resource management
• Best practices in exception handling

9. Introduction to Algorithms

• Definition and importance of algorithms
• Algorithm design principles
• Basic algorithmic techniques
  • Searching algorithms (e.g., linear and binary search)
  • Sorting algorithms (e.g., bubble sort, selection sort)
• Algorithm analysis basics (time and space complexity)

10. Debugging and Testing

• Importance of debugging and testing
• Common debugging techniques
• Testing methods
  • Unit testing
  • Integration testing
• Tools for debugging and testing
• Best practices to ensure code reliability