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Algorithms for Coding Interviews in C#

The ultimate guide to coding interviews in C#. Developed by FAANG engineers, it covers over 50 interactive challenges and solutions, helping you get interview-ready in just a few hours.

Intermediate

132 Lessons

14h

Certificate of Completion

The ultimate guide to coding interviews in C#. Developed by FAANG engineers, it covers over 50 interactive challenges and solutions, helping you get interview-ready in just a few hours.
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Explanations

AI-POWERED

Mock Interview

Explanations

This course includes

113 Playgrounds
42 Challenges
17 Quizzes
Course Overview
What You'll Learn
Course Content

Course Overview

With algorithms being one of the most common themes in coding interviews, having a firm grip on them can be the difference between being hired or not. After completing this comprehensive course, you’ll have an in-depth understanding of different algorithm types in C# and be equipped with a simple process for approaching complexity analysis. As you progress, you’ll be exposed to the most important algorithms you’ll likely encounter in an interview. You’ll work through over 50 interactive coding challenges a...Show More
With algorithms being one of the most common themes in coding interviews, having a firm grip on them can be the difference between being hired or not. After completing this comprehensive course, you’ll have an in-depth understanding of different algorithm ...Show More

What You'll Learn

Preparation for technical interviews at tech companies
An understanding of how to write fast and efficient code in C#
Working knowledge of fundamental algorithms using C#
The ability to assess the effectiveness of an algorithm
Familiarity with commonly used data structures
Preparation for technical interviews at tech companies

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Course Content

1.

Introduction

2 Lessons

Break down key algorithmic paradigms, asymptotic analysis, and common technical interview problems.

2.

Algorithmic Paradigms

4 Lessons

Solve challenges with brute force, greedy algorithms, divide and conquer, and dynamic programming approaches.

3.

Asymptotic Analysis

22 Lessons

Examine asymptotic analysis, Big O notation, and time complexity through practical examples and challenges.

4.

Sorting and Searching

24 Lessons

Break down complex ideas of sorting and searching algorithms through challenges and solutions.

5.

Graph Algorithms

20 Lessons

Solve problems in graph algorithms, including BFS, DFS, cycle detection, and graph transposition.

7.

Dynamic Programming

25 Lessons

Build on dynamic programming concepts with optimized algorithms for problems like Fibonacci, Knapsack, and Coin Change.

8.

Divide and Conquer

21 Lessons

Break down divide-and-conquer strategies, including binary search, GCD, and subarray problems.

9.

Conclusion

2 Lessons

Discover the logic behind efficient algorithms, their paradigms, and continuous improvement.

Course Author

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