Competitive Programming

准备好让您的编程技能更上一层楼了吗？在这门课程中，无论是新手还是高级程序员，您都将掌握必要的算法和数据结构，以便在比赛中取得好成绩并在软件面试中获得与其他候选人相比的竞争优势。

有许多技巧是通过经验获得的，竞争性程序员在将问题分解为构成解决方案的构建块时具有第六感，而且很多人不愿意分享这些技巧。在这里，我将让您了解对该领域有用的技术和应用程序，重点关注实际问题及其解决方法，同时让您直观地了解幕后发生的事情以及这些想法为何有效。

从动态规划到图算法和回溯，您将开始练习并对许多主题充满信心，学习诸如并查找不相交集、尝试和博弈论等高级概念而不会迷失，并在学习后立即应用新内容它有 100 多个建议的问题，包括过去的奥林匹克竞赛和在线评委，以及我专门为此课程创建的一些问题。所有这些都带有详细的解决方案。通过本课程，您将准备好参加在线竞赛和信息学奥林匹克竞赛，并将获得在该领域继续前进所需的经验。你准备好在你的旅程中迈出这重要的一步了吗？

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 48.0 KHz
Language: English | Size: 9.87 GB | Duration: 11h 34m

What you’ll learn
Competitive Programming
Algorithms
Data Structures
Programming
Merge Sort, QuickSort, Count Sort, Bucket Sort
Linear Search, Binary Search, QuickSelect, Two Pointer Technique
Stacks, Queues, Hash Tables, Hash Sets, Heap-Based Structures, Binary Search Tree-Based Data Structures, Coordinate Compression, Custom Comparators
Hash Functions, Collisions, Rabin-Karp, Sliding Window Technique
Greedy Algorithms
Iterative Complete Search, Backtracking, Permutations, Subsets, Pruning
Divide and Conquer, Binary Search the Answer, the Bisection Method
Dynamic Programming: Competitive Approach, Top-Down and Bottom-Up DP, Space Optimisation, Prefix Sums, Backtracking to Find Solutions
Graph Representation: Adjacency Lists, Adjacency Matrices, Edge Lists, Weighted and Unweighted Graphs
Graph Exploration: Breadth-First Search (BFS), Depth-First Search (DFS), Connected Components, Multi-Source BFS
Directed Graphs and Cycles: Topological Sort, Strongly Connected Components, BFS for Single-Source Shortest Paths
Shortest Paths: Dijkstra, Floyd-Warshall’s, Bellman-Ford and Negative-Weight Cycles, Arbitrages and the Logarithm Trick
Trees: Special Properties, Faster Shortest Paths, Diameter, Minimum Spanning Trees
Union-Find Disjoint Sets: Optimised Implementation, Kruskal’s Algorithm, Minimum Spanning Tree Variants
Strings: Dynamic Programming on Strings, Longest Common Subsequence, Edit Distance, Longest Palindromic Substring, Tries, Suffix Tries
Game Theory: States and Transitions, Minimax for Optimal Game Playing, Dynamic Programming To Recover Optimal Strategies
Approaching Interactive Problems

Description
Ready to take your programming skills to the next level? In this course, which will help both novice and advanced programmers alike, you will dominate the algorithms and data structures necessary to do well in contests and to gain a competitive edge over other candidates in software interviews.

There are many tricks which are gained through experience and competitive programmers have a sixth sense when it comes to breaking problems down into the building blocks that make up a solution and which many are reluctant to share. Here I will let you in on the techniques and the applications that are useful for the field, focusing on real problems and how they are solved, while giving you an intuition on what is going on under the hood and why these ideas work.

From dynamic programming to graph algorithms and backtracking, you will get to practise and feel confident about many topics, learning advanced concepts such as union-find disjoint sets, tries and game theory without feeling lost, and to apply new content as soon as you learn it, with over 100 suggested problems, both from past olympiads and online judges and some created by me specifically for this course. All of them come with detailed solutions. With this course, you will be ready to participate in online contests and informatics olympiads, and will have the experience necessary to continue advancing in this field. Are you ready to take this big step in your journey?

Who this course is for:
Students and engineers wishing to delve into competitive programming, diving into the details and soaring up the rankings
Developers with a desire to master algorithms to succeed in technical interviews
High school students with a passion for Mathematics interested in seeing algorithms applied to technology
Anyone interested in gaining insights and learning the details of algorithms and data structures