Expand your knowledge of problem solving and impress your coding interviewers.
What you will learn
Familiarity working with Arrays, Strings, Trees, Linked Lists and many other data structures
Exposure to the most common questions asked in interviews
Be able to critically analyze a problem and work towards an efficient solution
Learn numerous tricks which can be applied to the future questions you encounter
Gain the confidence and skills to ace your coding interviews
Consider time and space complexity when designing algorithms
Description
Welcome!
Hello everyone, and welcome to the course that will help you prepare for your coding interviews!
Specifically, we will be breaking down the easy collection of LeetCode’s Top Interview Questions playlist. This playlist includes 46 problems that are very commonly asked by interviewers from large tech companies such as Apple, Meta, Google, Uber, and many more! We will learn how to approach problems of all kinds, such as those consisting of Arrays, Strings, Linked Lists, Trees, Dynamic Programming, Design, Math, and general knowledge, while also learning useful concepts and tricks which will help when facing more difficult problems.
What is LeetCode?
Simply put, LeetCode is a large repository filled with interview questions asked by the top tech companies around the world (Google, Facebook, Amazon, and many more).
The main problem as a new user on LeetCode is that there are ENDLESS amounts of questions that you can find on there so you may not know which questions are the most common/beneficial to go over. This course’s purpose is to provide a solution to this issue, as I go over the Top Inteview Questions recommended by LeetCode. If you are looking to ace your upcoming coding interview or even just to strengthen your problem solving skills, then look no further as you have found the one-stop-shop to become a problem solving machine.
Course Overview
For each problem in the playlist, I have a video dedicated to explaining the thought process in detail which will lead us to the most efficient solution, paired with a visual to aid in explaining the algorithm. After we understand the approach for the most efficient solution, I will translate the visual into Java code, breaking down every line as I code it. After the entire solution is implemented, we will analyze the time and space complexity of the solution.
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