📘 Computer Science

Module I : Foundations of Computing (Low-Level & Memory)

• A. Binary Representation & Number Systems

  • Binary, Bytes, and Bitwise Operators in Python (Real Python)
  • Bitwise Operators in Python (AND, OR, XOR, NOT) (Real Python)
  • Base conversion (binaire, octal, hexadécimal) – YouTube (freeCodeCamp)
  • Numbers in Python (overview des types, int/float — Real Python)

• B. Floating Point & Numerical Precision

  • Floating-Point Representation Error (IEEE 754) (Real Python)
  • How to Round Numbers in Python (Real Python)

• C. Text Encoding & Unicode

  • Unicode & Character Encodings in Python (A Painless Guide) (Real Python)
  • ASCII & Unicode – YouTube

• D. Bytes, Serialization & Data Representation

  • Bytes Objects: Handling Binary Data in Python (Real Python)
  • Python’s Bytearray: A Mutable Sequence of Bytes (Real Python)
  • Serialize Your Data With Python (Real Python)

• E. Variables, References & Memory Model

  • Variables in Python (Real Python)
  • Pass-by-Reference in Python (Real Python)
  • Python’s Mutable vs Immutable Types (Real Python)
  • Python Copy: Shallow vs Deep Copy (Real Python)
  • Python’s del: Remove References From Scopes and Containers (Real Python)
  • Memory Management in Python (Real Python)
  • Pointers in Python: What’s the Point? (Real Python)

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Module II : Object-Oriented Programming

• A. Bases & modèle objet Python

  1. Object-Oriented Programming (OOP) in Python
  2. Python Classes: The Power of Object-Oriented Programming
  3. Variables in Python: Usage and Best Practices (références/aliasing utiles en POO)

• B. Construction & encapsulation

  1. Python Class Constructors: Control Your Object Instantiation
  2. Providing Multiple Constructors in Your Python Classes
  3. Python’s property(): Add Managed Attributes to Your Classes
  4. Getters and Setters: Manage Attributes in Python
  5. Single and Double Underscores in Python Names (API & pseudo-private)

• C. Reuse & organisation

  1. Inheritance and Composition: A Python OOP Guide
  2. What Are Mixin Classes in Python?
  3. What Does __init__.py Do? (packages)
  4. Namespaces in Python (portées/lookup d’attributs)

• D. Protocoles, datamodel & dunder

  1. Python’s Magic Methods: Leverage Their Power in Your Classes
  2. When Should You Use .repr() vs .str() in Python?
  3. Using Python’s .__dict__ to Work With Attributes
  4. Python Protocols: Leveraging Structural Subtyping (design orienté comportements)

• E. Qualité & design

  1. SOLID Principles: Improve Object-Oriented Design in Python
  2. Python’s Assignment Operator: Write Robust Assignments (effets de bord en POO)

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Module III : Core Data Structures & Algorithmic Thinking

• A. Panorama & bases

  1. Basic Data Types in Python: A Quick Exploration (Udemy – types numériques)
  2. Python Sequences: A Comprehensive Guide (pré-requis types + OOP)
  3. Python Mappings: A Comprehensive Guide (pré-requis types + OOP)

• B. Listes & tuples (séquences)

  1. Python’s list Data Type: A Deep Dive With Examples
  2. Lists vs Tuples in Python
  3. How to Use sorted() and .sort() in Python
  4. How to Split a Python List or Iterable Into Chunks
  5. How to Flatten a List of Lists in Python
  6. How to Remove Items From Lists in Python
  7. Python enumerate(): Simplify Loops That Need Counters
  8. Using the len() Function in Python
  9. Why Are Membership Tests So Fast for range() in Python?

• C. Dictionnaires (mappings)

  • 1. Dictionaries in Python
  • How to Iterate Through a Dictionary in Python
  • Sorting a Python Dictionary: Values, Keys, and More

• D. Ensembles (sets) & variantes légères

  1. Sets in Python
  2. Python Set Comprehensions: How and When to Use Them
  3. Write Pythonic and Clean Code With namedtuple
  4. Build Enumerations of Constants With Python’s Enum

• E. Chaînes & données binaires

  1. Strings and Character Data in Python
  2. How to Split a String in Python
  3. How to Join Strings in Python
  4. Efficient String Concatenation in Python
  5. How to Strip Characters From a Python String
  6. How to Replace a String in Python
  7. Bytes Objects: Handling Binary Data in Python
  8. Python’s Bytearray: A Mutable Sequence of Bytes
  9. Python’s Array: Working With Numeric Data Efficiently

• F. Itération & outils “batteries incluses”

  1. Iterators and Iterables in Python: Run Efficient Iterations
  2. Using the Python zip() Function for Parallel Iteration
  3. Python range(): Represent Numerical Ranges
  4. Python’s in and not in Operators: Check for Membership

• G. Mutabilité, copies & sécurité

  1. Python’s Mutable vs Immutable Types: What’s the Difference?
  2. How to Copy Objects in Python: Shallow vs Deep Copy Explained

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Module IV : Functional Programming

• A. Fondamentaux : Definition & Execution

  • Defining Your Own Python Function
  • Positional-Only and Keyword-Only Parameters in Python
  • What Are Python Asterisk and Slash Special Parameters For?

• B. Variables & portées

  • Python Scope & the LEGB Rule: Resolving Names in Your Code
  • Namespace in Python
  • The Python Global Keyword: Global Scope Beyond Functions
  • Using and Creating Global Variables in Your Python Functions

• C. Valeurs de retour, packing/unpacking & protocoles utiles

  • Using the Python zip() Function for Parallel Iteration
  • Python enumerate(): Simplify Loops That Need Counters
  • How to Use sorted() and .sort() in Python
  • Using the len() Function in Python
  • What Does isinstance() Do in Python?

• D. Fonctions d’ordre supérieur

  • Functions Are First-Class Citizens in Python
  • Functional Programming in Python: When and How to Use It
  • Python’s Built-in Functions: A Complete Exploration
  • Iterators and Iterables in Python: Run Efficient Iterations

• E. Fonctions anonymes, closures et décorateurs

  • Python Lambda Functions: How to Use Them Effectively
  • Python Closures: How to Use Them
  • How to Define and Use Python Decorators

• F. Récursion

  • Recursion in Python: An Introduction
  • Recursion Examples and Common Problems
  • Tail Recursion in Python: The Why and How

• G. Décorateurs

  • Primer on Python Decorators
  • Python Timer Functions: Three Ways to Monitor Your Code

• H. Générateurs, itérateurs & flux paresseux

  • Iterators and Iterables in Python: Run Efficient Iterations
  • Asynchronous Iterators and Iterables in Python

• I. Fonctions asynchrones : async def, await & coroutines

  • Python’s asyncio: A Hands-On Walkthrough
  • Speed Up Your Python Program With Concurrency

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Module V : Advanced Data Structures

• A. Introduction : structures et complexité

  1. Big O Notation in Python: A Complete Guide
  2. Common Python Data Structures

• B. Stack & Queue

  1. Python Stacks and Queues: A Step-by-Step Guide
  2. Python Stacks, Queues, and Priority Queues in Practice
  3. Working With collections.deque

• C. Linked Lists

  1. Python Linked Lists: Insert, Remove, Traverse, Reverse
  2. Build a Linked List Class From Scratch in Python

• D. Trees

  • Binary Trees in Python: Traversal, Insertion, and Search
  • Implementing a Binary Search Tree (BST) in Python
  • Tree Traversal Algorithms in Python: Preorder, Inorder, Postorder

• E. Graphs

  • Graphs in Python: Representation and Algorithms
  • Build a Maze Solver in Python Using Graphs (projet complet)
  • Depth-First Search (DFS) and Breadth-First Search (BFS) in Python

• F. Hashmaps (dictionnaires internes)

  • How Hash Tables Work in Python (and Beyond)
  • Python Dictionaries Under the Hood
  • Custom Python Dictionaries: Inheriting From dict vs UserDict
  • Implement hashmap using TDD

• G. Heaps & Priority Queues

  • Heaps in Python: Introduction to heapq
  • Priority Queues and Scheduling With heapq