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
Requirements
Some coding experince is required
Description
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.
Overview
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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