[New] The Python Programmer

Learn Python with Hands-On Practice: 100 Exercises and Over 20 Code Challenges to Sharpen Your Skills

What you'll learn

You will gain practical knowledge and experience with Python programming language from fundamentals to advanced topics.

Practice with 100 code exercises and over 20 code challenges with written test cases.

Learn how to design and build real-world applications using Python.

Learn Python's best practices and how to develop clean Python code.

Learn how to apply Object-Oriented Programming and Functional Programming in Python.

Requirements

No programming experience needed. You will learn everything you need to know.

A Mac or PC computer with internet access

No paid software required. You will learn how to use the VS Code editor for writing Python programs

Description

Whether you're planning to work in software development, data science, data analytics, or simply want to learn programming, The Python Programmer course is designed to equip you with the expertise needed to develop Python professionally. This course is more than just theory – it's a hands-on journey through Python's core and advanced features, preparing you for real-world applications.With 15+ chapters, you'll explore everything from basic syntax to advanced topics. You’ll solve 100 exercises, test your knowledge with 150+ MCQs,  and optionally solve 20+ coding challenges. Each chapter is packed with practical exercises, code challenges, and quizzes that will test and solidify your understanding of Python.This course comes with customised learning journeys to help you achieve your goals efficiently. We start with programming fundamentals like data types, control flows, and data-structures, and then progress to object-oriented programming and advanced topics like decorators, generators, and concurrency. You'll also gain valuable experience by applying Python to real-world problems, ensuring you're ready for any Python-related task in your career.Whether you want to enhance your programming skills or learn about some advanced topics in Python, I've incorporated all of my knowledge and experience into this course to ensure it provides the tools and confidence you need to succeed. I hope you enjoy this course and get the best experience out of this journey!Shehab

Overview

Section 1: Introduction

Lecture 1 Who is this course for?

Lecture 2 How to take this course?

Section 2: Introduction to Python

Lecture 3 What is Python?

Lecture 4 Ways of Running Python Code

Lecture 5 Setting up your Python environment

Lecture 6 Download the Exercises

Lecture 7 How to Solve the Exercises

Lecture 8 Python Comments

Lecture 9 Coding Setup!

Section 3: Variables & Data Types

Lecture 10 What is a variable?

Lecture 11 Primitive datatypes

Lecture 12 Type Conversion

Lecture 13 Literals & Constants

Lecture 14 Built-in Functions

Lecture 15 Base Conversion

Lecture 16 Wrap Up

Lecture 17 Coding Time!

Lecture 18 Solutions (chapter02_variables)

Section 4: Operators

Lecture 19 Intro to Operators

Lecture 20 Arithmetic Operators

Lecture 21 Assignment Operators

Lecture 22 Relational Operators

Lecture 23 Logical Operators

Lecture 24 Bitwise Operators

Lecture 25 Identity Operators

Lecture 26 Membership Operators

Lecture 27 Wrap Up

Lecture 28 Coding Time!

Lecture 29 Solutions (chapter03_operators)

Section 5: Control Flow

Lecture 30 Intro to Control Flow

Lecture 31 Conditional statements (if, elif, else)

Lecture 32 Structural Pattern Matching

Lecture 33 Loops

Lecture 34 for-loop

Lecture 35 while-loop

Lecture 36 Break, continue, and pass statements

Lecture 37 Wrap Up

Lecture 38 Coding Time!

Lecture 39 Solutions (chapter04_control_flow)

Section 6: Functions

Lecture 40 Intro to Functions

Lecture 41 Types of Function Arguments

Lecture 42 Lamda Functions

Lecture 43 Scope

Lecture 44 Using `nonlocal`

Lecture 45 Using `global`

Lecture 46 Pass By Object Reference

Lecture 47 Recursion

Lecture 48 Recursive vs Iterative Functions

Lecture 49 Type Hinting

Lecture 50 Wrap Up

Lecture 51 Coding Time!

Lecture 52 Solutions (chapter05_functions)

Section 7: Python datastructures

Lecture 53 Intro to Data structures

Lecture 54 Lists

Lecture 55 Nested Lists

Lecture 56 List Comprehension

Lecture 57 Dictionaries

Lecture 58 Dict Comprehension

Lecture 59 Sets

Lecture 60 Set Comprehension

Lecture 61 Tuples

Lecture 62 Intro to `collections` module (defaultdict, ordereddict, counter, deque)

Lecture 63 Wrap Up

Lecture 64 Coding Time!

Lecture 65 Solutions (chapter06_datastructures)

Section 8: Strings

Lecture 66 Strings Recap

Lecture 67 String Indexing

Lecture 68 String Slicing

Lecture 69 String Formatting

Lecture 70 Wrap Up

Lecture 71 Coding Time!

Lecture 72 Solutions (chapter07_strings)

Section 9: Working with Files

Lecture 73 Working with Files

Lecture 74 Reading from Files

Lecture 75 Writing to Files

Lecture 76 Paths in Python

Lecture 77 Context Managers

Lecture 78 Wrap Up

Lecture 79 Coding Time!

Lecture 80 Solutions (chapter08_files)

Section 10: Error & Exception Handling

Lecture 81 Intro to Exceptions

Lecture 82 Try, except, else, finally

Lecture 83 Custom Exceptions

Lecture 84 Exception Groups

Lecture 85 Wrap Up

Lecture 86 Coding Time!

Lecture 87 Solutions (chapter09_error_handling)

Section 11: Object Oriented Programming

Lecture 88 Intro to OOP

Lecture 89 Classes & Objects

Lecture 90 Instance vs Class variables

Lecture 91 Instance, Static, and Class methods

Lecture 92 Dunder methods (e.g. `__init__()`)

Lecture 93 Inheritance & Polymorphism

Lecture 94 Abstract Classes

Lecture 95 Class Generics

Lecture 96 Enums

Lecture 97 Protocols (Duck Typing)

Lecture 98 Wrap Up

Lecture 99 Coding Time!

Lecture 100 Solutions (chapter10_oop)

Section 12: Python Standard Libraries

Lecture 101 Intro to Standard Libraries

Lecture 102 Using `dataclasses`

Lecture 103 Using `datetime`

Lecture 104 Using `functools`

Lecture 105 Using `itertools`

Lecture 106 Using `logging`

Lecture 107 Using `timeit`

Lecture 108 Using `pickle`

Lecture 109 Coding Time!

Lecture 110 Solutions (chapter11_standard_library)

Section 13: Advanced Functions

Lecture 111 Higher-order Functions

Lecture 112 Closures

Lecture 113 Iterators

Lecture 114 Generators

Lecture 115 Decorators

Lecture 116 Wrap Up

Lecture 117 Coding Time!

Lecture 118 Solutions (chapter12_advanced_functions)

Section 14: Modules and Packages

Lecture 119 Intro to Modules & Packages

Lecture 120 What is __name__ == "__main__"?

Lecture 121 What is `PYTHONPATH`?

Lecture 122 What is PyPi?

Lecture 123 site-packages vs dist-packages

Lecture 124 Wrap Up

Lecture 125 Coding Time!

Lecture 126 Solutions (chapter13_modules_and_packages)

Section 15: Testing

Lecture 127 What is testing?

Lecture 128 Testing in Python

Lecture 129 Writing a test using `unittest`

Lecture 130 Writing a test using `pytest`

Lecture 131 What is Test-Driven Development (TDD)?

Lecture 132 Wrap Up

Lecture 133 Coding Time!

Lecture 134 Solutions (chapter14_testing)

Section 16: Concurrency & Parallelism

Lecture 135 Intro to Concurrency & Parallelism

Lecture 136 Intro to Threading

Lecture 137 Intro to Asynchronous Programming

Lecture 138 AsyncIO and Async/Await

Lecture 139 Intro to Global Interpreter Lock (GIL)

Lecture 140 Why do we need threading.Lock() if we have GIL?

Lecture 141 Intro to Multiprocessing

Lecture 142 Intro to `concurrent.futures` (Thread/Process Pool Executor)

Lecture 143 When to use Threading vs Multiprocessing vs Async?

Lecture 144 Wrap Up

Lecture 145 Coding Time!

Lecture 146 Solutions (chapter15_concurrency)

Section 17: Congratulations!

Lecture 147 Congratulations!

Lecture 148 Next Steps

First-time learners who want to learn programming in Python.,Beginner Python developers who want to practice and advance their Python knowledge and skills.