• Introduction to Python:

1. History and features of Python programming language
2. Setting up the development environment
3. Running Python scripts and interactive mode

• Variables and Data Types:

1. Understanding variables and their usage
2. Numeric data types (integers, floats, etc.)
3. Strings and string manipulation
4. Boolean data type and logical operations

• Control Structures:

1. Conditional statements (if, elif, else)
2. Looping structures (for loops, while loops)
3. Control flow (break, continue)

• Lists and Tuples:

1. Creating and manipulating lists
2. List comprehension
3. Understanding tuples and their immutability

• Dictionaries and Sets:

1. Working with dictionaries (key-value pairs)
2. Dictionary manipulation and iteration
3. Sets and their operations (union, intersection, etc.)

• Functions and Modules:

1. Defining and calling functions
2. Function parameters and return values
3. Modular programming using modules and importing

• File Handling:

1. Reading from and writing to files
2. File modes and operations (read, write, append)
3. Handling file exceptions

• Exception Handling:

1. Understanding exceptions and their types
2. Using try-except blocks to handle exceptions
3. Handling multiple exceptions and custom exceptions

• Object-Oriented Programming (OOP) Basics:

1. Introduction to OOP concepts (classes, objects, methods)
2. Encapsulation, inheritance, and polymorphism
3. Class attributes and instance attributes

• OOP Advanced Concepts:

1. Class inheritance and method overriding
2. Abstract classes and interfaces
3. Class composition and aggregation

• Recursion:

1. Understanding recursion and recursive functions
2. Recursive algorithms and problem-solving techniques

• String Manipulation:

1. String methods and operations
2. String formatting and interpolation
3. Regular expressions for advanced string manipulation

• Sorting and Searching Algorithms:

1. Sorting algorithms (e.g., bubble sort, merge sort)
2. Searching algorithms (e.g., linear search, binary search)
3. Analyzing algorithm complexity (Big O notation)

• Data Structures - Stack and Queue, Linked List, Trees, Graphs:

1. Understanding and implementing stack and queue data structures
2. Linked list operations (insertion, deletion, traversal)
3. Introduction to tree and graph data structures

• File Handling and Data Serialization:

1. Working with files and directories
2. Serializing data using pickle and JSON

• Regular Expressions:

1. Introduction to regular expressions and their syntax
2. Pattern matching and substitution using regular expressions

• Debugging and Testing:

1. Debugging techniques and tools
2. Unit testing using the unittest module

• Mini Projects:

1. Implementing small projects to apply learned concepts
2. Enhancing problem-solving and coding skills.