Complete Python Programming : From Basics To Advance

Complete Guide to Python: Fundamentals, Automation, OS Interaction, Multithreading, and Optimization Strategies

What you'll learn

Build a strong foundation in Python syntax, variables, data types, lists, tuples, and dictionaries.

Master tabular data handling with NumPy arrays and nested lists for memory-efficient processing.

Capture and process images using OpenCV and NumPy for computer vision applications.

Understand multithreading and how Python handles CPU-bound vs. I/O-bound operations.

Optimize programs for better CPU and memory usage through profiling and efficient design patterns.

Differentiate between concurrency and parallelism with visual demos and OS-level tools.

Prepare for advanced topics like multiprocessing, async programming, and quantum computing.

Requirements

No prior programming experience required. This course starts from scratch and gradually builds up to advanced topics.

Description

"Complete Python: From Basics to Advance" is a comprehensive, hands-on course that guides you through the journey of mastering Python, from the fundamentals to advanced topics like system automation and optimization. Whether you're a complete beginner or an experienced developer, this course will provide you with the tools and techniques to harness the full power of Python.Begin by learning the basics, including variables, data types, loops, and functions, before diving into more advanced topics like object-oriented programming and Python libraries. As you progress, you'll explore core Python concepts like file handling, error handling, and working with APIs. You’ll also gain a strong understanding of data structures such as lists, dictionaries, and sets, enabling you to build efficient and scalable systems.The course also covers crucial skills for system automation, such as writing scripts to control your OS, automate repetitive tasks, and interact with external systems. You’ll delve into multithreading for performance optimization, memory profiling, and advanced topics like concurrency. The course also prepares you for real-world applications of Python, like automating workflows, managing files, and building AI-powered applications.By the end of this course, you'll be proficient in Python and able to develop programs that optimize your system’s performance, automate complex workflows, and solve real-world problems effectively. Perfect for aspiring developers, automation enthusiasts, and anyone looking to enhance their Python programming skills.

Overview

Section 1: Python Programming

Lecture 1 Master Python: From Zero to Pro - Complete Practical Course & Project-Based Lear

Lecture 2 Understanding Programming Languages with Python

Lecture 3 1_3. Python

Lecture 4 Python Programming: Variables, Data Types, Type Inference & System Command

Lecture 5 Master Functions & TTS in Python using Modules, Libraries & pyttsx3

Lecture 6 Automate WhatsApp with Python: Step-by-Step

Lecture 7 Python Data Structures Demystified |Array, Memory, RAM and Real-World Automation

Lecture 8 Arrays, Lists, and Tuples for Secure and Efficient Coding | Cryptography Concept

Lecture 9 Mastering Lists & Nested Lists for Tabular Data - Practical Guide & Challenge!

Lecture 10 Nested Lists, Column Operations & Why Choos Data Structure (like NumPy) Matters

Lecture 11 From Lists to NumPy Arrays for Efficient Tabular Data & Image Cropping!

Lecture 12 Capture Webcam Images & Basic Image Processing | Computer Vision Tutorial

Lecture 13 Python Images and OpenCV: Understanding Image as Data Arrays and Beyond

Lecture 14 Generating Images with NumPy and Steganography Concepts in Python

Lecture 15 Python Deep Dive: Dynamic Typing, Type Hinting & Real-World Automation

Lecture 16 In-Depth: Polymorphism, Powerful String & List Methods, and Dynamic Exploration

Lecture 17 Building a Voice-Controlled OS Automation App & Data Structures(Lists vs Tuples)

Lecture 18 Building an OS Automation App with if-else, User Input & System Commands

Lecture 19 Building an AI-Powered OS Automation Tool | Natural Language & Voice Commands

Lecture 20 Conditional Logic Deep Dive: Boolean, None, Functions & Tricky if/else Puzzles

Lecture 21 Python Conditionals: Inline if/else, Ternary Operators & Functional Programming

Lecture 22 Python Logic: AND, OR, NOT & Lazy Evaluation for Smarter Coding

Lecture 23 Mastering if-else, Boolean Operations, and the in Operator |Programming Tutorial

Lecture 24 Building AI-Powered Automation - From Mic Input to Text (Speech-to-Text)

Lecture 25 From Voice to Text with PyAudio & Google API | AI & NLP Tutorial

Lecture 26 Integrating Speech Recognition & Intro to with Statement and Loops

Lecture 27 Infinite Loops, break, else & Voice App Demo | Python Programming Tutorial

Lecture 28 Understanding Iteration with for vs. while for Powerful Data Processing

Lecture 29 Python for Loops: True Iteration, enumerate, Iterables & Conditional Logic

Lecture 30 Advanced Python for Loops: Iterators, List Comprehensions, break & continue

Lecture 31 Generators & yield: Deep Dive into Iterators, Memory Efficiency, and Function

Lecture 32 Master Iterators, State Preservation & Memory Efficiency

Lecture 33 Generators Explained: Master yield for Memory-Efficient Iteration & Lazy Evaluat

Lecture 34 Mastering Memory-Efficient Lazy Evaluation for High Performance Code

Lecture 35 Mastering Memory Profiling with memory_profiler & Understanding Decorators

Lecture 36 Profiling Memory, Execution Time, and Mastering Lambda Functions in Python

Lecture 37 Lambda, Higher-Order Functions, and Real-World Filtering

Lecture 38 Optimizing RAM & CPU Usage - Understanding Variables, References & PVM Internals

Lecture 39 Understanding Variables, References, id(), hex(), and Shallow Copying with copy

Lecture 40 Master Memory & Copy in Python: Shallow vs Deep with Image Use Cases

Lecture 41 Sequential Execution, Infinite Loops, Real-World Problem Solving | Deep Dive

Lecture 42 Organizing Data with Key-Value Structures for Robust Programming

Lecture 43 Dictionary Operations: Zipping-Unzipping, Merging & Column-Oriented Data Structu

Lecture 44 Dictionaries vs. DataFrames: When and Why to Use for Row and Column Operation

Lecture 45 Deep Dive: Local vs. Global Variables, Stack Memory & the __name__ Attribute

Lecture 46 Global Variables, Scope, Namespaces & Variable Arguments (*args)

Lecture 47 Variable Arguments (*args, **kwargs), Parameter Order & Intro to Concurrency

Lecture 48 Achieving Concurrency and Parallelism through Context Switching

Lecture 49 Understanding Multithreading, Processes, and CPU Behavior in Python

Lecture 50 Mastering Multithreading in Python: From Single Thread to Concurrent Execution

Lecture 51 Advanced Multithreading in Python and the Illusion of Parallelism

Lecture 52 Understanding CPU Architecture, Hardware Threads and Foundation of Multithreadin

Lecture 53 Global Interpreter Lock (GIL) in Python and Limitations of True Multithreading

Lecture 54 Demystifying Python Multithreading Performance: Time Sharing vs True Parallelism

Python Developers,Automation Engineers,Backend Developers,Software Engineers,Tech Interviewees,AI Developers,Machine Learning Practitioners,Beginners