Data Structures & Algorithms with Python Guide

• 1. Introduction to Arrays and Lists
• 2. Lists — Creation, Indexing and Basic Operations
• 3. Complexity of List Operations
• 4. Advanced Slicing
• 5. List Comprehensions
• 6. Tuples vs Lists — Mutability and Semantics
• 7. Linear Search and the array Module
• 8. Module Project — Data Processor with Lists

• 1. Introduction to Stacks, Queues and Linked Lists
• 2. Stacks — LIFO from Scratch
• 3. Classic Stack Problems
• 4. Queues — FIFO and collections.deque
• 5. Singly Linked List from Scratch
• 6. Doubly Linked List and Trade-offs
• 7. Array vs Linked List — When to Use Each One
• 8. Module Project — Task Manager with Undo and a Processing Queue

• 1. Introduction to Trees and Binary Search Trees
• 2. Binary Trees — Concepts and Structure
• 3. BST — Insert and Search
• 4. BST — Delete (The 3 Cases)
• 5. Traversals — Inorder, Preorder, Postorder (DFS)
• 6. BFS and Level-by-Level Traversal
• 7. Balance, Height and Degenerate Trees
• 8. Module Project — Complete BST with Visualization

• 1. Introduction to Hash Tables
• 2. Hash Functions — How to Turn Keys into Indexes
• 3. Implementing a Hash Table with Chaining
• 4. Open Addressing and Linear Probing
• 5. Load Factor and Rehashing
• 6. Dict and Set — Usage Patterns in Backend
• 7. Classic Problems with Hash Tables
• 8. Project — Complete Hash Table + Solved Problems

• 1. Introduction to Sorting, Searching and Big O
• 2. Big O Notation — The Language of Efficiency
• 3. Bubble Sort and Insertion Sort — Quadratic Algorithms
• 4. Merge Sort — Divide and Conquer
• 5. Quick Sort — Pivots and Partitions
• 6. Binary Search — Searching in O(log n)
• 7. Integrated Comparison and Analysis
• 8. Project — Sorting & Searching Library

• 1. Introduction to the Algorithm Playground
• 2. Project Structure — Professional Organization
• 3. Integrating the Data Structures
• 4. Integrating the Sorting Algorithms
• 5. Integrating Searching and Classic Problems
• 6. Tests with pytest — Verify Everything
• 7. Benchmarks and Documentation — The Professional Touch
• 8. Final Project — The Complete Algorithm Playground

No limit. It's a free guide: come in whenever you like, as often as you like.

No. Modules run from easier to harder, but you can jump to the one you need. Progress is saved per lesson.

Whatever is needed is listed under “What you need to bring”, above. If nothing is listed there, you can start from zero.

In the Club's WhatsApp group, and every two weeks there's a live with an instructor where questions get worked through.

No. This guide is self-paced with no dates. The bootcamp is live, by cohort, with work someone reviews.