Young India Fellow at the Ashoka University. Former Computer Engineering Undergrad at the Delhi Technological University. 

Sanket Kashyap

Ultimate guide to acing the coding interview, a very dynamic course presented to you by Sanket Kashyap. All those aspirants who feel that they need some more preparation to get into their dream company and to top in the coding interview, this would be a perfect course. This course initiates with the lesson through which you will learn the concepts of linked lists. After you attain the theoretical knowledge on linked list, next unit focusses on some typical problems on linked lists. The next topic taught by him is on binary trees, which is then followed by binary search trees, heap, binary search, merge sort, quick sort, dynamic programming levelling up DP, the greedy paradigm, bitwise tricks introduction to graphs, Breadth First Search and Depth First Search. These are the topics which you will study in this entire course. Sanket also invites some of his Friends who have placed in the top companies like Google, Amazon to talk about the importance of certain coding concepts which one must know while appearing for the interviews.

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In this lesson, the educator talks about the objective of the course he is teaching and for whom it will be beneficial. This lesson also tells you about what one would gain after watching this course. He also talks about the various topics he would be teaching in his upcoming lessons. 

Overview Of The Course: Ultimate Guide To Acing A Coding Interview

This lesson provides a basic introduction of Linked Lists. The lesson talks about what a linked list is, how do we define a linked list and finally how to add nodes to a linked list along with various illustrations. The educator also throws light on the importance of linked lists in tech interviews by giving an example.

Starting With Linked Lists

This lesson discusses a few classic problems which are usually hard for newcomers. The problems covered are how to detect a cycle in a Linked List, how to find the merge point of two Linked Lists and finally how to merge two sorted linked lists. All the concepts are explained with illustrations for a clearer understanding. 

Typical Problems On Linked Lists

Binary Trees are one of the most important data structures out there with respect to the interview preparation. This lesson begins with a brief introduction to the formal and informal explanation of binary trees. It also throws light on the structure of a tree, adding a new node and all the other basic terminology associated with a Binary Tree.

Binary Trees: Meaning And Associated Terminology

Binary Search Trees are a data structure that is a Binary Tree and follows certain rules which make it unique on its own. This lesson talks about the formal and informal meaning of Binary Search Tree. It also throws light on searching in a Binary Search Tree and writing code. Understand the different ways of traversing the Binary search trees: Inorder, Preorder and Postorder Traversal. Also understand how to delete a Binary search trees.

Binary Search Trees: Writing, Traversing And Deleting

Heaps are another Data Structure whose structure is very similar to that of a Binary Tree but the functions of a Heap make it very unique. The lesson begins with the informal and formal meaning of Heaps and thereby elaborating upon the types of heaps which are explained with the help of illustrations. Understand the implementation of Heaps from scratch in this lesson.

Heaps: Meaning, Types & Implementation

One of the most beautiful and powerful algorithms out there. Binary Search radically decreases the time required to search for an element in the array and is a very often used algorithm to reduce time complexity in coding questions. The lesson talks about the Trivial Linear Search and developing the intuition with the help of an example. The educator talks about writing a code and understanding how efficient it is. Also, learn about the simple Binary search tasks. 

Importance Of Binary Search

The Mergesort is a sorting algorithm that is a brilliant manifestation of the Divide and Conquer programming paradigm. The lesson starts with a basic discussion on Sorting and slowly and intuitively builds up the idea for Mergesort. Then we discuss the time complexity of this algorithm owing to its complex nature.

Mergesort: Meaning & Implementation

Quicksort is another sorting algorithm that explores the Divide and Conquer programming paradigm. This sort is a fast and efficient algorithm and the time complexity analysis for this is slightly different as compared to other sorting algorithms. In this lesson, you will learn what is a quicksort and how does Divide and Conquer work here.  You will also learn how to code the final Quicksort function. A reference code is provided with the sort too.

Quicksort: Meaning & Coding

One of the most important techniques to have in your arsenal. This lesson lays the stepping stones for further Dynamic Programming problems by explaining the hallmarks, Optimal Substructure, and Overlapping Subproblems, with Fibonacci numbers.

Introduction To Dynamic Programming

In this lesson, we cover some classical Dynamic Programming problems and discuss their code. The first problem covered is the Minimum Cost Path in a Matrix which is a very commonly repeated interview question. Thereby, the Longest Common Subsequence Problem, a real classic problem is discussed. Again variations of this are frequently asked in interviews. The last problem discussed is The Longest Increasing Subsequence Problem.

Levelling Up In Dynamic Programming

After learning how to create solutions for each and every state and then levelling them up to the required final state in Dynamic Programming, this lesson we learn a method called Greedy Algorithms. While similar to Dynamic Programming in a few aspects Greedy algorithms works much faster. In this lesson understand what is a Greedy Strategy and the required properties which are explained with the help of an example. This lesson also talks about the difference in the solution using Greedy Strategy and using Dynamic Programming. 

Learn The Greedy Programming Paradigm

Bitwise operations are faster than normal arithmetic operations. These operations are also used to perform some otherwise tedious operations much faster. In this lesson, we catch up on some tricks after revising the bitwise operators.

Learn Bitwise Operations Tricks

Graphs are a very versatile data structure in themselves. In addition to that Graphs are very frequently used in real life problems. In this lesson, we discuss the basics of a graph and how to represent it in its two most common forms ­ the Adjacency Lists and the Adjacency Matrix.

Introduction To Graph Theory

Searching a graph is a very important topic as a programmer. Knowledge of these algorithms is the crux of graphs. The lesson starts with the what, why and how of Breadth First Search commonly known as BFS after that we move on to the second algorithm, Depth First Search commonly known as DFS and observe their working. The algorithms are supplemented with their pseudocodes to enhance understanding of these algorithms.

Breadth First Search And Depth First Search

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General intelligence and general mathematics.

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Lessons

15 lessons • 1h 48m