Mastering Python Programming 2024

Most Comprehensive Python Programming Course

What you'll learn

Understand Python's foundational concepts and its unique advantages in programming, enabling them to apply Python in diverse fields effectively.

Apply core Python programming constructs, such as data types, variables, operators, and control structures, to create robust and efficient code.

Implement Object-Oriented Programming (OOP) principles in Python, including inheritance, encapsulation, and polymorphism, to design modular and reusable code.

Develop skills in functional programming by using advanced concepts like lambda functions, map, filter, reduce, & comprehensions for cleaner and efficient code

Work confidently with data structures in Python (lists, tuples, sets, dictionaries) and use them effectively for various applications.

Handle exceptions and errors gracefully to create more reliable and user-friendly programs.

Leverage Python for file operations, data serialization, and deserialization for data storage, retrieval, and processing.

Explore Python's concurrency and parallelism capabilities using multithreading and synchronization techniques to write faster, more responsive applications.

Use iterators and generators for memory-efficient data handling and implement custom iterators.

Apply Python modules and packages to organize code effectively and make use of third-party libraries for extending Python's capabilities.

By the end, you will be able to confidently build, debug, and optimize Python applications, making them well-equipped for real-world Python development

Requirements

No programming experience is needed. This course starts from the basics and gradually builds up, covering everything you need to know to become proficient in Python.

Description

Welcome to Mastering Python Programming, an all-encompassing course designed to take you from a complete beginner to a confident Python programmer. This course offers a thorough journey through Python, starting with foundational concepts and progressing to advanced topics that will prepare you to tackle real-world problems and projects. You’ll learn not only the essentials, such as data types, control structures, and functions, but also delve into key areas like Object-Oriented Programming, functional programming, and data structures such as lists, tuples, and dictionaries. With hands-on coding exercises and practical examples, you’ll gain a solid foundation to apply Python confidently in various fields, from web development and automation to data analysis and more.In addition to the core Python concepts, this course covers specialized skills, including working with files, handling errors gracefully, and leveraging Python’s powerful libraries and modules. You’ll explore advanced topics such as iterators, generators, multithreading, and even functional programming techniques like map, filter, and lambda expressions. We’ll guide you through creating efficient, reusable code using Python’s object-oriented features and introduce you to professional practices for code reuse, modularization, and debugging. Whether you're aiming to launch a career in tech, automate workflows, or simply expand your programming expertise, this course provides all the tools and knowledge needed to master Python and use it to create dynamic, high-performance applications.

Overview

Section 1: Ab Initio Of Python

Lecture 1 Introduction To Python

Lecture 2 What Sets Python Apart

Lecture 3 Where Is Python Used

Lecture 4 Getting Started With Python

Lecture 5 Python Resources

Lecture 6 Python Compilation Process

Lecture 7 Working With Python

Section 2: Python Basics

Lecture 8 Python Identifiers And Keywords

Lecture 9 Python Types

Lecture 10 Arithmetic Operators

Lecture 11 Conversion Functions

Lecture 12 Builtin Functions

Lecture 13 Builtin Modules

Lecture 14 Container Types

Lecture 15 Comments, Indentation And Multilining

Lecture 16 Classes And Objects

Lecture 17 Strings

Lecture 18 String Methods

Section 3: Decision Control Instructions

Lecture 19 Decision Control Instruction

Lecture 20 Logical Expressions

Lecture 21 Conditional Expressions

Section 4: Loop Control Instructions

Lecture 22 Repetition Control Instruction

Lecture 23 The For Loop

Section 5: Console Input/Output

Lecture 24 Console Input

Lecture 25 Console Output

Lecture 26 Console Output Examples

Section 6: Lists

Lecture 27 Python Lists

Lecture 28 Lists And Builtin Functions

Lecture 29 List Methods

Lecture 30 List Miscellany

Lecture 31 Stack And Queue Using List

Section 7: Tuples

Lecture 32 Python Tuples

Lecture 33 Tuples And Builtin Functions

Lecture 34 Tuples Miscellany

Lecture 35 List Of Tuples And Vice Versa

Section 8: Sets

Lecture 36 Python Sets

Lecture 37 Common Set Operations

Lecture 38 Sets And Builtin Functions And Methods

Lecture 39 Typical Set Operations

Section 9: Dictionaries

Lecture 40 Python Dictionaries

Lecture 41 Dictionary Operations

Lecture 42 Dictionary Built-in Functions And Methods

Lecture 43 Dictionary Varieties

Section 10: Comprehensions

Lecture 44 Python Comprehensions

Lecture 45 List Comprehensions

Lecture 46 Set Comprehensions

Lecture 47 Dictionary Comprehensions

Section 11: Functions

Lecture 48 Python Functions

Lecture 49 Communication With Functions

Lecture 50 Variable Length Arguments

Lecture 51 Default Values For Function Arguments

Lecture 52 Mixing Argument Types

Lecture 53 Unpacking Function Arguments

Section 12: Recursion In Python

Lecture 54 Recursion

Lecture 55 When To Use Recursion

Lecture 56 Recursion - Similar Sub Problems

Lecture 57 Working Of Similar Sub Problems

Lecture 58 Recursion - Unknown Number Of Loops

Lecture 59 Types Of Recursion

Section 13: Functional Programming

Lecture 60 Functional Programming in Python

Lecture 61 Lambda Functions

Lecture 62 Map Filter Reduce Operations

Lecture 63 Map Filter Reduce Functions

Lecture 64 Lambda And Map Filter Reduce

Section 14: 14. Modules And Packages

Lecture 65 Python Modules

Lecture 66 Module Import

Lecture 67 Multiple Ways To Use A Module

Lecture 68 Packages

Lecture 69 Symbol Table

Lecture 70 Namespace

Lecture 71 Locals And Globals

Lecture 72 Types Of Scopes

Section 15: OOP With Python

Lecture 73 Object Oriented Programming

Lecture 74 Classes And Objects In Python

Lecture 75 User Defined Classes

Lecture 76 Object Iniialization

Lecture 77 Class Variables And Methods

Lecture 78 Vars And Dir Functions

Lecture 79 Identifier Naming Convention

Lecture 80 Operator Overloading

Lecture 81 Everything Is An Object

Lecture 82 Handling Dissimilar Data

Lecture 83 Type Conversion

Section 16: Code Reuse In Python

Lecture 84 Reuse Mechanisms

Lecture 85 Containership

Lecture 86 Inheritance

Lecture 87 Inheritance Access

Lecture 88 Inheritance Types

Lecture 89 Diamond Problem

Lecture 90 Inheritance Miscellany

Lecture 91 Abstract Classes

Section 17: Iterators and Generators

Lecture 92 Iterables And Iterators

Lecture 93 User Defined Iterators

Lecture 94 Generators

Lecture 95 Generator Expressions

Lecture 96 Zip Function

Section 18: Exception Handling

Lecture 97 Errors And How To Tackle Them

Lecture 98 Exception Handling

Lecture 99 Exception Handling Nuances

Lecture 100 User Defined Exceptions

Lecture 101 Else And Finally Blocks

Lecture 102 Exception Handling Tips

Section 19: Input/Output In Python

Lecture 103 IO System

Lecture 104 Read Write Operations

Lecture 105 File Opening Modes

Lecture 106 File Seek Operations

Lecture 107 Serialization / Deserialization

Lecture 108 Complex Serialization / Deserialization

Lecture 109 Serialization Of User Defined Types

Lecture 110 File And Directory Operations

Section 20: Miscellaneous Features Of Python

Lecture 111 Documentation Strings

Lecture 112 Command Line Arguments

Lecture 113 Bitwise Operators

Lecture 114 Assertion

Lecture 115 Decorators

Lecture 116 Decorators For Funcs WIth Args

Lecture 117 Unicode

Lecture 118 Creating Executable File

Section 21: Concurrency And Parallelism

Lecture 119 Concurrency And Parallelism

Lecture 120 Multithreading

Lecture 121 IOBound And CPUBound Programs

Lecture 122 Ways To Improve Program Performance

Lecture 123 Types Of Concurrencies

Lecture 124 Thread Properties

Lecture 125 Ways To Launch Threads

Section 22: Thread Synchronization

Lecture 126 Synchronization

Lecture 127 Synchronization Using Locks

Lecture 128 Synchronization Using RLocks

Lecture 129 Semaphores

Lecture 130 Inter Thread Communication

Lecture 131 Producer Consumer Algorithm

Aspiring engineers, data scientists, and data analysts interested in learning Python as it is a primary language in data analysis, machine learning, and artificial intelligence.,Students and professionals looking to add Python programming to their skill set to automate tasks, analyze data, or move further in tech roles.,Software developers and IT professionals from other programming languages who want to learn Python to expand their programming skillset or transition into roles that require Python expertise.,Educators and teachers who want to gain a structured understanding of Python to teach programming or enhance computational thinking in the classroom.,The course is structured to gradually increase in difficulty, ensuring that you gain new skills and insights.