Top interview coding problems Must do Rock coding 12 wks

Top 85-100 interview coding questions, major algorithms and data structures in simple way. FAANG. Java implementation.
Top interview coding problems Must do Rock coding 12 wks
File Size :
6.35 GB
Total length :
19h 44m



Rheme Inc


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Top interview coding problems Must do Rock coding 12 wks

What you’ll learn

Spend only 1-3 weeks to get fully prepared for a coding interview
Learn, implement and use different data structures and algorithms
Rock your interview coding skill and chances to get the top paid job
Become a better developer by mastering computer science fundamentals
Solve up to 100 top typical interview coding problems and algorithms in top companies, including FAANG

Top interview coding problems Must do Rock coding 12 wks


Some coding experince is required


Everything up the point to get a dream job and pass coding interview.This course is designed to help you master coding interview questions commonly asked by top technology companies. Whether you are a beginner or experienced programmer, this course will provide you with the knowledge and skills necessary to excel in coding interviews.Our expert instructors have carefully curated a list of the top 85-100 coding problems frequently asked in interviews. Through a combination of video lectures and hands-on coding exercises, you will learn how to approach each problem, identify the most efficient algorithm, and implement the solution in a variety of programming languages.Our course will help you build your confidence and enhance your problem-solving skills, which are essential for success in any coding interview. With our step-by-step guidance, you will develop the necessary skills to solve complex coding problems with ease.By enrolling in this course, you will be equipped with the knowledge and skills to land your dream job at top tech companies. Spend 2-4 hours daily during 1-3 weeks and you will get your dream job.Here is what topics you will learn in this course :1. Big O notation2. Data structures:  . * Arrays     * Hash Tables     * Singly Linked Lists     * Doubly Linked Lists     * Queues     * Stacks     * Trees      * Min-heap and Max-heap     * Tries     * Graphs3. Algorithms:     * Recursion     * Sorting     * Searching     * Sliding Window algorithm     * Xor Bit algorithm      * Expand around center algorithm     * Knuth-Morris-Pratt (KMP) Algorithm     * Rabin-Karp String Matching Algorithm     * Hashing     * Linked List and Tree Traversal     * Breadth First Search     * Depth First Search     * Dynamic Programming     * Devide and Conquer algorithm     * Hoare’s Quickselect Algorithm    * Floyd’s  Cycle Detection Algorithm    * Bellman-Ford Algorithm    * Dijkstra’s Algorithm    * Topological Sort Algorithm    * Two Pointers algorithmTaught by:Sergiy is the instructor with 20+ years of experince in IT. Sergiy has been working as a senior, principal software developer and architect in financial companies for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life.


Section 1: Introduction

Lecture 1 Introduction

Section 2: Course Material

Lecture 2 Github sourse code URL

Lecture 3 source code zip

Lecture 4 Recommended books and sites for practice

Section 3: Easy to Medium Problems

Lecture 5 Two Sum. Caching data.

Lecture 6 Finding duplicates. BitSet algorithm

Lecture 7 Pairs

Lecture 8 Squares of a Sorted Array.

Lecture 9 Romans to integers

Lecture 10 Valid Parentheses. Data stacking algorithm

Lecture 11 Best time to buy and sell the stock.

Lecture 12 Reverse String. Two pointers algorithm

Lecture 13 Valid Palindrome.

Lecture 14 Single Number. Xor Bit Algorithm.

Lecture 15 Contains Duplicates

Lecture 16 First Unique Character in a String

Lecture 17 Intersection of 2 arrays

Lecture 18 Majority Element

Lecture 19 sqrtX

Lecture 20 Missing Number

Lecture 21 Climbing steps

Lecture 22 Plus one

Lecture 23 Linked List Cycle. Cache and Floyd’s Cycle Finding Algorithms

Lecture 24 Happy Number

Lecture 25 Intersection of 2 linked lists

Lecture 26 Reversed linked list

Lecture 27 Reversed doubly linked list

Lecture 28 Reverse singly linked list in groups of k

Lecture 29 Move last node to the front

Lecture 30 Delete Node in a Linked List

Lecture 31 Palindrome Linked list

Lecture 32 Pascal triangle

Lecture 33 Missing Ranges

Lecture 34 Longest Common Prefix. Scanning & Devide and Conquer algorithm

Lecture 35 Binary Tree. BFS

Lecture 36 Binary Tree. DFS

Lecture 37 Binary Tree height

Lecture 38 N-tree max depth

Lecture 39 Binary Tree list per level. 2 Queue pointers

Lecture 40 Same Binary Trees

Lecture 41 Binary Tree serialization

Lecture 42 Unique Binary Tree serialization

Lecture 43 Binary Tree subtree

Lecture 44 Merkle Tree in blockchain and distributed systems. Hashing

Lecture 45 Symmetric Tree

Lecture 46 BST validation

Lecture 47 Kth largest element in BST. Reverse-In-Order traversal algorithm

Lecture 48 Sorted array to BST

Lecture 49 Balanced Binary Tree.

Lecture 50 Build graph. Adjacency matrix and Adjacency List representation

Lecture 51 Graph : BFS Algorithm traversal

Lecture 52 Graph : DFS Algorithm traversal

Lecture 53 Directed Graph Path

Lecture 54 DAG graph : Topological Sort

Section 4: Medium problems

Lecture 55 Three sum

Lecture 56 Reverse Integer

Lecture 57 Container with the most water

Lecture 58 Longest unique substring. Sliding Window algorithm.

Lecture 59 Longest palindromic substring Part 1.

Lecture 60 Longest palindromic substring Part 2. Dynamic Programming

Lecture 61 String pattern match Part1. KMP algorithm

Lecture 62 LRU cache Part 1. Ordered Dictionary solution.

Lecture 63 LRU cache Part 2. DoublyLinkedList and Map solution

Lecture 64 String Pattern match Part 2. Rabin-Karp String Matching Algorithm

Lecture 65 MinHeap and MaxHeap. Heap sort

Lecture 66 Convert a max heap into a min heap. HeapifyMin and HeapifyMax algorithm.

Lecture 67 Kth Smallest Element in a Sorted Matrix Part 1. Min-heap Approach

Lecture 68 Kth Smallest Element in a Sorted Matrix Part 2. Binary Search Algorithm

Lecture 69 Top K Frequent Elements. Heap Algorithm.

Lecture 70 Merge Intervals

Lecture 71 Unique Paths. Dynamic Programming.

Lecture 72 Rotate Array / Image

Lecture 73 Number of Islands Part1. DFS approach

Lecture 74 Number of Islands Part2. BFS approach.

Lecture 75 Meeting Rooms Part1. Priority Queues

Lecture 76 Meeting Rooms Part2. Chronological Order

Lecture 77 Find the Celebrity

Lecture 78 Course Schedule. Topological Sort

Lecture 79 Coin Change Part1. Recursive solution

Lecture 80 Coin Change Part2. Dynamic Programming

Lecture 81 Sort List. Merge Sort

Lecture 82 Design Tic-Tac-Toe

Lecture 83 Design Twitter

Lecture 84 Implement Trie (Prefix Tree)

Section 5: Appendix

Lecture 85 Recursion

Lecture 86 Arrays

Lecture 87 java.util

Lecture 88 Streams

Lecture 89 Dates

Lecture 90 Sorting

Lecture 91 Searching

All levels who is looking for to get prepared for a coding interview and improve understanding of data structures and algorithms

Course Information:

Udemy | English | 19h 44m | 6.35 GB
Created by: Rheme Inc

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