Sep

10

2021

Competitive Programming

Laser 10 Sep 2021 18:09 LEARNING » e-learning - Tutorial

Competitive Programming
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 9.87 GB | Duration: 11h 34m

Ready to take your programming skills to the next level

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 Strats

Approaching Interactive Problems

Description

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 eeers 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




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