Intermédiaire

Data Structures and Algorithms — Level 2

Tries, union-find, shortest paths, greedy, backtracking, dynamic programming, segment trees and more: advanced problem solving in Python or Java.

0.0(0 avis) 0 élève

Créé par Ouissem BEN HENIA

Mis à jour le novembre 2026 Disponible en

Ce que vous apprendrez

Apply a 6-step method to any algorithmic problem, from brute force to the right structure
Use balanced trees, tries, union-find, Fenwick and segment trees where they shine
Find shortest paths, minimum spanning trees and topological orders in graphs
Design greedy, divide-and-conquer, backtracking and dynamic-programming solutions
Analyse amortized and recursive costs, and explain your solution in an interview
Build a city route planner with Dijkstra, a heap, a trie and an LRU cache

Choisissez votre pile

Ce cours s'adapte à vous : choisissez une filière, puis une technologie par groupe. Le sommaire, votre progression et votre certificat suivent votre choix.

Programming language

The concept videos are shared; pick the language of the code, the library videos and the labs.

Conseillé avant Data Structures and Algorithms — Level 1

Aperçu du contenu pour Data Structures and Algorithms — Level 2 — Python

Vidéos

Quiz

Labs

10h 43min

Durée totale

Contenu du cours

7 sections • 97 leçons • 10h 43min au total

The Problem-Solving MethodAperçu7min
Quiz · The Problem-Solving MethodAperçu5min
Advanced Analysis: Amortized Cost and Recursion TreesAperçu7min
Quiz · Advanced Analysis: Amortized Cost and Recursion TreesAperçu5min
Measuring Recursion and Amortized Cost in Python7min
Quiz · Measuring Recursion and Amortized Cost in Python5min
Lab · Amortized cost and recursion costs10min

Prérequis

Data Structures and Algorithms — Level 1 (or equivalent)
Comfortable with Python or Java

Description

Go from knowing data structures to solving hard problems. Each topic starts with a shared concept video (the idea, the animation, the cost and the real use cases) and continues in Python or Java: build it, use the standard library, solve the problem and avoid the traps. A step-by-step method for any problem, interview corners, and a capstone route planner with Dijkstra, a heap and a trie.

À qui s'adresse ce cours

Developers preparing for coding interviews
Students of computer science and competitive programming
Engineers who want to solve harder problems with confidence

Formateur

Ouissem BEN HENIA

8 cours • 7 élèves • 0 ★

★ 0.0 · 0 avis

Ce que vous apprendrez

Apply a 6-step method to any algorithmic problem, from brute force to the right structure

Use balanced trees, tries, union-find, Fenwick and segment trees where they shine

Find shortest paths, minimum spanning trees and topological orders in graphs

Design greedy, divide-and-conquer, backtracking and dynamic-programming solutions

Analyse amortized and recursive costs, and explain your solution in an interview

Build a city route planner with Dijkstra, a heap, a trie and an LRU cache

Contenu du cours

7 sections • 97 leçons • 10h 43min au total

The Problem-Solving MethodAperçu7min
Quiz · The Problem-Solving MethodAperçu5min
Advanced Analysis: Amortized Cost and Recursion TreesAperçu7min
Quiz · Advanced Analysis: Amortized Cost and Recursion TreesAperçu5min
Measuring Recursion and Amortized Cost in Python7min
Quiz · Measuring Recursion and Amortized Cost in Python5min
Lab · Amortized cost and recursion costs10min

Description