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What you'll learn?
- You will learn all you need to know about the variety of programming competitions that exist, as well as basic algorithms and data structures necessary to succeed in the most popular of them.
- The benefits of participating in programming competitions
- The algorithms and approaches you need to master the world of competitions
- Ways of self-training for further progress
Course Overview
Competitive programming is an exciting and rewarding activity. Besides improving your knowledge of algorithms and programming languages, it gives you unique experience of problem-solving, thinking out of the box and working to tough deadlines – all essential for boosting your value as a programmer or computer scientist.
You will learn all you need to know about the variety of programming competitions that exist, as well as basic algorithms and data structures necessary to succeed in the most popular of them.
This course can be taken by anyone either who is a beginner or knows programming but lacks some concept that they need to know in order to succeed in most of them.
Pre-requisites
- Just your dedication and your love to code
- Basic knowledge of any common programming language (C++, Java, Python)
Target Audience
- Do you want your programming skills to be challenged and taken to a new level? Are you ready to prove your excellence to thousands of fellow programmers around the globe? If so, this course is just for you!
Curriculum 27 Lectures 03:37:31
-
Section 1 : Welcome to Competitive Programming
- Lecture 2 :
- What and How to do ?
-
Section 2 : Intro to Coding Websites
-
Section 3 : Computational Complexity and Data Structures
- Lecture 1 :
- Big O notation and computational complexity
- Lecture 2 :
- Linear Data Structure overview
- Lecture 3 :
- Vectors
- Lecture 4 :
- Lists
- Lecture 5 :
- Stack, Queue and Deque
-
Section 4 : Sorting part: I
- Lecture 1 :
- Introduction to sorting
- Lecture 2 :
- Insertion Sort
- Lecture 3 :
- When do sort?
- Lecture 4 :
- Quick Sort
- Lecture 5 :
- Quick Sort Modification
- Lecture 6 :
- Merge Sort
-
Section 5 : Sorting part: II
- Lecture 1 :
- Lower Bound, Stable Sorting, Comparator
- Lecture 2 :
- Integer Sorting
- Lecture 3 :
- Sorting Guidelines
- Lecture 4 :
- Introduction to Binary Search
- Lecture 5 :
- Implementation of Binary Search
- Lecture 6 :
- Priority Queue and Binary Heap
-
Section 6 : Graph Theory: I
- Lecture 1 :
- Introduction to Graphs
- Lecture 2 :
- Graphs: Representation in Memory
- Lecture 3 :
- Introduction to Depth First Search
- Lecture 4 :
- Depth First Search with Timestamps
- Lecture 5 :
- Topological Sort
- Lecture 6 :
- Introduction to Dynamic Programming
-
Section 7 : Graph Theory: II
- Lecture 1 :
- Eulerian Paths & Eulerian Tours
- Lecture 2 :
- Hamiltonian Path & Hamiltonian Tour
Our learners work at
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