Gain insights into competitive programming, explore C++ skills with theory, code samples, practice problems, and master faster implementation for contests like ACM ICPC, Google CodeJam, and HackerCup.

Competitive programming can be a great way to build out your programming skills, get on any major company’s radar, and earn a little extra cash along the way.

In this course, you will learn to prepare for competitive programming contests like ACM ICPC, Google CodeJam, Facebook HackerCup, and many more.

Each topic is broken down with a healthy mix of theory, code samples, step-by-step solved sample problems, illustrations, useful practice problems, and tips and tricks for faster implementation.

You will need some solid C++ foundations coming into this course, but by the end it, you will be confident enough in your C++ skills to take home the win.

Competitive Programming in C++: The Keys to Success

## How does the above chart help me?

When competing in contests,  your solution is given a fixed time of a few seconds to execute and produce the correct output. The time taken to execute is directly dependent on the number of operations your algorithm performs. Hopefully this chart helps you understand how different runtimes grow in the number of operations with growing N relative to each other.


# Is my solution going to run in time?
The actual answer will depend on a number of factors like hidden constants, allowed execution time, and the server where the code is executed.

Nevertheless, below is a general rule of thumb to determine whether your solution is going to run in time, given that the time constraint is only a few seconds:



|**N**|**Acceptable**|
|----:|:------------:|
|$10^7$|$O(N)$|
|$10^6$|$O(N*logN)$|
|$10^5$|$O(N*log^2N)$, $O(N*\sqrt{N})$|
|$10^4$|$O(N^2)$|
|$10^3$|$O(N^2*logN)$|
|$10^2$|$O(N^3)$|
|$20 - 25$|$O(2^N)$|
|$20$|$O(2^N*N)$|
|$10$|$O(N^6)$, $O(N!)$|

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In this lesson, we'll compare solutions with different runtimes.



Introduction

Complexity Analysis

Number Theory

Arrays and Vectors

Sieve of Eratosthenes

Strings

Sorting

Linked List

Stack

Queue

Binary Tree

2 Pointers

Heap

Binary Search Tree

Balanced Binary Search Tree

Course Conclusion

Comparing Runtimes

Visualizing runtimes #

How does the above chart help me?

Is my solution going to run in time?