Python syllabus : Latest Updated Syllabus for syllabus

Topic

Description

Python Overview

• Brief history of Python, its creator (Guido van Rossum), and its design philosophy (readability, simplicity, and versatility). 
• Highlight Python's strengths, such as interpreted nature, dynamically-typed, and cross-platform compatibility.

Python Installation

• Step-by-step guide to installing Python on different operating systems (Windows, macOS, and Linux). 
• Cover different installation methods (e.g., official Python installer, package managers like apt or brew).

Python Interpreter

• Understand the Python interpreter and its usage.
• Learn basic commands like print() and executing Python files.

Python Syntax

Learn Python's syntax rules, including indentation (whitespace instead of braces), comments (single-line and multi-line), and basic structure of a Python program.

Data Types

• Python's built-in data types: integers, floats, strings, booleans, and their respective operations. 
• Learn about type conversion functions like int(), float(), and str().

Variables and Expressions

• Learn how to define variables and assign values to them. 
• Check variable naming conventions and rules. 
• Cover arithmetic expressions, operator precedence, and type conversion in expressions.

Topic

Description

Conditional Statements

• Learn how to use if, elif, and else statements for decision-making based on conditions. 
• Cover Boolean expressions, logical operators (and, or, not), and comparison operators (==, !=, >, , >=, ).

Loops

• Learn the for loop for iterating over sequences (strings, lists, tuples, etc.) and the while loop for executing code as long as a condition is true. 
• Cover the range() function and its usage with loops.

Break and Continue

• Learn the use of break and continue statements in loops. 
• break terminates the loop, while continue skips the current iteration and moves to the next one.

Functions

• Define and call functions, including the use of parameters and return values. 
• Learn the importance of functions for code reusability and modularity. 
• Cover function arguments (positional, keyword, and default arguments).

Scope

• Understand the concept of variable scope in Python: global, local, and nonlocal. 
• Learn the rules for accessing and modifying variables in different scopes.

Recursion

• Understand recursive functions and their applications. Explain base cases and recursive cases. 
• Practice problems that can be solved using recursion (e.g., factorial, Fibonacci sequence).

Topic

Description

Lists

• Cover creating lists, accessing elements by index, slicing, and common list methods (e.g., append(), insert(), remove(), sort(), reverse()). 
• Explain list comprehension as a concise way of creating lists.

Tuples

• Learn the usage of tuples for storing related data and their advantages over lists in certain scenarios.
• Cover tuple unpacking and tuple methods.

Dictionaries

Cover creating dictionaries, accessing and modifying values using keys, and common dictionary methods (e.g., keys(), values(), items()).

Sets

• Learn set operations like union, intersection, difference, and their applications. 
• Cover set methods like add(), remove(), and discard().

String Manipulation

Explore various string operations and methods, such as string formatting, slicing, splitting, joining, and common string methods (e.g., strip(), replace(), find()).

List Comprehension

Revisit list comprehension as a concise way of creating lists based on existing sequences or conditions.

Topic

Description

Classes and Objects

• Learn how classes define the blueprint for objects, and objects are instances of classes. 
• Cover class attributes and methods, creating objects, and accessing object attributes and methods.

Inheritance

• Learn the concept of inheritance as a way to create new classes based on existing ones. 
• Cover single inheritance, multiple inheritance, and multi-level inheritance. 
• Discuss the use of the super() function and method overriding.

Polymorphism

• Polymorphism is the ability of objects to take on multiple forms. 
• Explain method overloading (not supported in Python) and method overriding (supported in Python).

Encapsulation

• Encapsulation is a way to hide implementation details and control access to class members. 
• Learn the use of private (__) and protected (_) attributes and methods.

Special Methods

Special methods (also known as magic methods or dunder methods) in Python, such as __init__() for object initialization, __str__() for string representation, and __len__() for defining length.

Exception Handling

• Cover exception handling in Python using the try, except, finally, and raise statements. 
• Learn built-in exceptions and create custom exceptions. 
• Check the importance of error handling in robust code.

Topic

Description

File Operations

• File operations in Python, including opening files using the open() function, reading from files using read() or readline(), and writing to files using write(). 
• Cover closing files with the close() method.

File Modes

• Learn different file modes in Python, such as r (read), w (write), a (append), b (binary), and their combinations (e.g., rb, wb, ab). 
• Cover the implications of each mode and when to use them.

Modules and Packages

• Learn the concept of modules in Python as reusable code libraries. 
• Cover creating modules, importing modules using the import statement, and accessing module contents. 
• Check packages to organize related modules.

Standard Library

• Python's standard library includes a vast collection of built-in modules for various tasks, such as file and directory operations, mathematics, networking, and more. 
• Check some commonly used modules.

Third-Party Libraries

• Cover installing third-party libraries using package managers like pip. 
• Learn about popular libraries like NumPy, Pandas, Matplotlib and their applications.

Topic

Description

Generators and Iterators

• Generators are a way to create iterators, which are objects that can be iterated over. 
• Learn how to use the yield keyword to create generator functions and expressions. 
• Learn the advantages of generators, such as memory efficiency and lazy evaluation.

Decorators

• Decorators are a way to modify the behaviour of functions without changing their source code. 
• Cover function decorators and their syntax using @decorator_name. 
• Discuss use cases for decorators, such as logging, caching, and authentication.

Lambda Functions

• lambda functions (anonymous functions) are a concise way to define small, one-line functions. Learn their syntax and common use cases, such as with higher-order functions (e.g., map(), filter(), reduce()).

Regular Expressions

• Regular expressions (regex) are a powerful tool for pattern matching and text processing. 
• Learn the basic syntax and meta-characters used in regular expressions. 
• Cover the re-module and its functions for working with regular expressions.

Multithreading and Multiprocessing

• Concurrent programming in Python, including multithreading and multiprocessing. 
• Learn the difference between threads and processes and their use cases. 
• Cover the threading and multiprocessing modules, and synchronization primitives like locks and semaphores.