The Complete Data Structures And Algorithms Course In Python

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The Complete Data Structures And Algorithms Course In Python
Last updated 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 9.33 GB | Duration: 46h 37m
100+ DSA Interview Questions for Cracking FAANG with Animated Examples for Deeper Understanding and Faster Learning​

What you'll learn
Learn, implement, and use different Data Structures
Learn, implement and use different Algorithms
Become a better developer by mastering computer science fundamentals
Learn everything you need to ace difficult coding interviews
Cracking the Coding Interview with 100+ questions with explanations
Time and Space Complexity of Data Structures and Algorithms
Recursion
Big O
Requirements
Basic Python Programming skills
Description
Welcome to the Complete Data Structures and Algorithms in Python Bootcamp, the most modern, and the most complete Data Structures and Algorithms in Python course on the internet.At 40+ hours, this is the most comprehensive course online to help you ace your coding interviews and learn about Data Structures and Algorithms in Python. You will see 100+ Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft and how to face Interviews with comprehensive visual explanatory video materials which will bring you closer towards landing the tech job of your dreams!Learning Python is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! This course will help you in better understanding every detail of Data Structures and how algorithms are implemented in high level programming language.We'll take you step-by-step through engaging video tutorials and teach you everything you need to succeed as a professional programmer.After finishing this course, you will be able to:Learn basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applicationsLearn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasetsLearn how to apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.Why this course is so special and different from any other resource available online?This course will take you from very beginning to a very complex and advanced topics in understanding Data Structures and Algorithms!You will get video lectures explaining concepts clearly with comprehensive visual explanations throughout the course.You will also see Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft.I cover everything you need to know about technical interview process!So whether you are interested in learning the top programming language in the world in-depthAnd interested in learning the fundamental Algorithms, Data Structures and performance analysis that make up the core foundational skillset of every accomplished programmer/designer or software architect and is excited to ace your next technical interview this is the course for you!And this is what you get by signing up today:Lifetime access to 40+ hours of HD quality videos. No monthly subscription. Learn at your own pace, whenever you wantFriendly and fast support in the course Q&A whenever you have questions or get stuckFULL money back guarantee for 30 days!Who is this course for?Self-taught programmers who have a basic knowledge in Python and want to be professional in Data Structures and Algorithms and begin interviewing in tech positions!As well as students currently studying computer science and want supplementary material on Data Structures and Algorithms and interview preparation for after graduation!As well as professional programmers who need practice for upcoming coding interviews.And finally anybody interested in learning more about data structures and algorithms or the technical interview process!This course is designed to help you to achieve your career goals. Whether you are looking to get more into Data Structures and Algorithms , increase your earning potential or just want a job with more freedom, this is the right course for you!The topics that are covered in this course.Section 1 - IntroductionWhat are Data Structures?What is an algorithm?Why are Data Structures and Algorithms important?Types of Data StructuresTypes of AlgorithmsSection 2 - RecursionWhat is Recursion?Why do we need recursion?How Recursion works?Recursive vs Iterative SolutionsWhen to use/avoid Recursion?How to write Recursion in 3 steps?How to find Fibonacci numbers using Recursion?Section 3 - Cracking Recursion Interview QuestionsQuestion 1 - Sum of DigitsQuestion 2 - PowerQuestion 3 - Greatest Common DivisorQuestion 4 - Decimal To BinarySection 4 - Bonus CHALLENGING Recursion Problems (Exercises)power factorial productofArray recursiveRange fib reverse isPalindrome someRecursive flatten captalizeFirst nestedEvenSum capitalizeWords stringifyNumbers collectStringsSection 5 - Big O NotationAnalogy and Time ComplexityBig O, Big Theta and Big OmegaTime complexity examplesSpace ComplexityDrop the Constants and the non dominant termsAdd vs MultiplyHow to measure the codes using Big O?How to find time complexity for Recursive calls?How to measure Recursive Algorithms that make multiple calls?Section 6 - Top 10 Big O Interview Questions (Amazon, Facebook, Apple and Microsoft)Product and SumPrint PairsPrint Unordered PairsPrint Unordered Pairs 2 ArraysPrint Unordered Pairs 2 Arrays 100000 UnitsReverseO(N) EquivalentsFactorial ComplexityFibonacci ComplexityPowers of 2Section 7 - ArraysWhat is an Array?Types of ArrayArrays in MemoryCreate an ArrayInsertion OperationTraversal OperationAccessing an element of ArraySearching for an element in ArrayDeleting an element from ArrayTime and Space complexity of One Dimensional ArrayOne Dimensional Array PracticeCreate Two Dimensional ArrayInsertion - Two Dimensional ArrayAccessing an element of Two Dimensional ArrayTraversal - Two Dimensional ArraySearching for an element in Two Dimensional ArrayDeletion - Two Dimensional ArrayTime and Space complexity of Two Dimensional ArrayWhen to use/avoid arraySection 8 - Python ListsWhat is a List? How to create it?Accessing/Traversing a listUpdate/Insert a ListSlice/ from a ListSearching for an element in a ListList Operations/FunctionsLists and stringsCommon List pitfalls and ways to avoid themLists vs ArraysTime and Space Complexity of ListList Interview QuestionsSection 9 - Cracking Array/List Interview Questions (Amazon, Facebook, Apple and Microsoft)Question 1 - Missing NumberQuestion 2 - PairsQuestion 3 - Finding a number in an ArrayQuestion 4 - Max product of two intQuestion 5 - Is UniqueQuestion 6 - PermutationQuestion 7 - Rotate MatrixSection 10 - CHALLENGING Array/List Problems (Exercises)Middle Function2D ListsBest ScoreMissing NumberDuplicate NumberPairsSection 11 - DictionariesWhat is a Dictionary?Create a DictionaryDictionaries in memoryInsert /Update an element in a DictionaryTraverse through a DictionarySearch for an element in a DictionaryDelete / Remove an element from a DictionaryDictionary MethodsDictionary operations/ built in functionsDictionary vs ListTime and Space Complexity of a DictionaryDictionary Interview QuestionsSection 12 - TuplesWhat is a Tuple? How to create it?Tuples in Memory / Accessing an element of TupleTraversing a TupleSearch for an element in TupleTuple Operations/FunctionsTuple vs ListTime and Space complexity of TuplesTuple QuestionsSection 13 - Linked ListWhat is a Linked List?Linked List vs ArraysTypes of Linked ListLinked List in the MemoryCreation of Singly Linked ListInsertion in Singly Linked List in MemoryInsertion in Singly Linked List AlgorithmInsertion Method in Singly Linked ListTraversal of Singly Linked ListSearch for a value in Single Linked ListDeletion of node from Singly Linked ListDeletion Method in Singly Linked ListDeletion of entire Singly Linked ListTime and Space Complexity of Singly Linked ListSection 14 - Circular Singly Linked ListCreation of Circular Singly Linked ListInsertion in Circular Singly Linked ListInsertion Algorithm in Circular Singly Linked ListInsertion method in Circular Singly Linked ListTraversal of Circular Singly Linked ListSearching a node in Circular Singly Linked ListDeletion of a node from Circular Singly Linked ListDeletion Algorithm in Circular Singly Linked ListMethod in Circular Singly Linked ListDeletion of entire Circular Singly Linked ListTime and Space Complexity of Circular Singly Linked ListSection 15 - Doubly Linked ListCreation of Doubly Linked ListInsertion in Doubly Linked ListInsertion Algorithm in Doubly Linked ListInsertion Method in Doubly Linked ListTraversal of Doubly Linked ListReverse Traversal of Doubly Linked ListSearching for a node in Doubly Linked ListDeletion of a node in Doubly Linked ListDeletion Algorithm in Doubly Linked ListDeletion Method in Doubly Linked ListDeletion of entire Doubly Linked ListTime and Space Complexity of Doubly Linked ListSection 16 - Circular Doubly Linked ListCreation of Circular Doubly Linked ListInsertion in Circular Doubly Linked ListInsertion Algorithm in Circular Doubly Linked ListInsertion Method in Circular Doubly Linked ListTraversal of Circular Doubly Linked ListReverse Traversal of Circular Doubly Linked ListSearch for a node in Circular Doubly Linked ListDelete a node from Circular Doubly Linked ListDeletion Algorithm in Circular Doubly Linked ListDeletion Method in Circular Doubly Linked ListEntire Circular Doubly Linked ListTime and Space Complexity of Circular Doubly Linked ListTime Complexity of Linked List vs ArraysSection 17 - Cracking Linked List Interview Questions (Amazon, Facebook, Apple and Microsoft)Linked List ClassQuestion 1 - Remove DupsQuestion 2 - Return Kth to LastQuestion 3 - PartitionQuestion 4 - Sum Linked ListsQuestion 5 - IntersectionSection 18 - StackWhat is a Stack?Stack OperationsCreate Stack using List without size limitOperations on Stack using List (push, pop, peek, isEmpty, )Create Stack with limit (pop, push, peek, isFull, isEmpty, )Create Stack using Linked ListOperation on Stack using Linked List (pop, push, peek, isEmpty, )Time and Space Complexity of Stack using Linked ListWhen to use/avoid StackStack QuizSection 19 - QueueWhat is Queue?Queue using Python List - no size limitQueue using Python List - no size limit , operations (enqueue, dequeue, peek)Circular Queue - Python ListCircular Queue - Python List, Operations (enqueue, dequeue, peek, )Queue - Linked ListQueue - Linked List, Operations (Create, Enqueue)Queue - Linked List, Operations (Dequeue(), isEmpty, Peek)Time and Space complexity of Queue using Linked ListList vs Linked List ImplementationCollections ModuleQueue ModuleMultiprocessing moduleSection 20 - Cracking Stack and Queue Interview Questions (Amazon,Facebook, Apple, Microsoft)Question 1 - Three in OneQuestion 2 - Stack MinimumQuestion 3 - Stack of PlatesQuestion 4 - Queue via StacksQuestion 5 - Animal ShelterSection 21 - Tree / Binary TreeWhat is a Tree?Why Tree?Tree TerminologyHow to create a basic tree in Python?Binary TreeTypes of Binary TreeBinary Tree RepresentationCreate Binary Tree (Linked List)PreOrder Traversal Binary Tree (Linked List)InOrder Traversal Binary Tree (Linked List)PostOrder Traversal Binary Tree (Linked List)LevelOrder Traversal Binary Tree (Linked List)Searching for a node in Binary Tree (Linked List)Inserting a node in Binary Tree (Linked List)Delete a node from Binary Tree (Linked List)Delete entire Binary Tree (Linked List)Create Binary Tree (Python List)Insert a value Binary Tree (Python List)Search for a node in Binary Tree (Python List)PreOrder Traversal Binary Tree (Python List)InOrder Traversal Binary Tree (Python List)PostOrder Traversal Binary Tree (Python List)Level Order Traversal Binary Tree (Python List)Delete a node from Binary Tree (Python List)Entire Binary Tree (Python List)Linked List vs Python List Binary TreeSection 22 - Binary Search TreeWhat is a Binary Search Tree? Why do we need it?Create a Binary Search TreeInsert a node to BSTTraverse BSTSearch in BSTDelete a node from BSTDelete entire BSTTime and Space complexity of BSTSection 23 - AVL TreeWhat is an AVL Tree?Why AVL Tree?Common Operations on AVL TreesInsert a node in AVL (Left Left Condition)Insert a node in AVL (Left Right Condition)Insert a node in AVL (Right Right Condition)Insert a node in AVL (Right Left Condition)Insert a node in AVL (all together)Insert a node in AVL (method)Delete a node from AVL (LL, LR, RR, RL)Delete a node from AVL (all together)Delete a node from AVL (method)Delete entire AVLTime and Space complexity of AVL TreeSection 24 - Binary HeapWhat is Binary Heap? Why do we need it?Common operations (Creation, Peek, sizeofheap) on Binary HeapInsert a node in Binary HeapExtract a node from Binary HeapDelete entire Binary HeapTime and space complexity of Binary HeapSection 25 - TrieWhat is a Trie? Why do we need it?Common Operations on Trie (Creation)Insert a string in TrieSearch for a string in TrieDelete a string from TriePractical use of TrieSection 26 - HashingWhat is Hashing? Why do we need it?Hashing TerminologyHash FunctionsTypes of Collision Resolution TechniquesHash Table is FullPros and Cons of Resolution TechniquesPractical Use of HashingHashing vs Other Data structuresSection 27 - Sort AlgorithmsWhat is Sorting?Types of SortingSorting TerminologiesBubble SortSelection SortInsertion SortBucket SortMerge SortQuick SortHeap SortComparison of Sorting AlgorithmsSection 28 - Searching AlgorithmsIntroduction to Searching AlgorithmsLinear SearchLinear Search in PythonBinary SearchBinary Search in PythonTime Complexity of Binary SearchSection 29 - Graph AlgorithmsWhat is a Graph? Why Graph?Graph TerminologyTypes of GraphGraph RepresentationCreate a graph using PythonGraph traversal - BFSBFS Traversal in PythonGraph Traversal - DFSDFS Traversal in PythonBFS Traversal vs DFS TraversalTopological SortTopological Sort AlgorithmTopological Sort in PythonSingle Source Shortest Path Problem (SSSPP)BFS for Single Source Shortest Path Problem (SSSPP)BFS for Single Source Shortest Path Problem (SSSPP) in PythonWhy does BFS not work with weighted Graphs?Why does DFS not work for SSSP?Dijkstra's Algorithm for SSSPDijkstra's Algorithm in PythonDijkstra Algorithm with negative cycleBellman Ford AlgorithmBellman Ford Algorithm with negative cycleWhy does Bellman Ford run V-1 times?Bellman Ford in PythonBFS vs Dijkstra vs Bellman FordAll pairs shortest path problemDry run for All pair shortest pathFloyd Warshall AlgorithmWhy Floyd Warshall?Floyd Warshall with negative cycle,Floyd Warshall in Python,BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall,Minimum Spanning Tree,Disjoint Set,Disjoint Set in Python,Kruskal Algorithm,Kruskal Algorithm in Python,Prim's Algorithm,Prim's Algorithm in Python,Prim's vs KruskalSection 30 - Greedy AlgorithmsWhat is Greedy Algorithm?Well known Greedy AlgorithmsActivity Selection ProblemActivity Selection Problem in PythonCoin Change ProblemCoin Change Problem in PythonFractional Knapsack ProblemFractional Knapsack Problem in PythonSection 31 - Divide and Conquer AlgorithmsWhat is a Divide and Conquer Algorithm?Common Divide and Conquer algorithmsHow to solve Fibonacci series using Divide and Conquer approach?Number FactorNumber Factor in PythonHouse RobberHouse Robber Problem in PythonConvert one string to anotherConvert One String to another in PythonZero One Knapsack problemZero One Knapsack problem in PythonLongest Common Sequence ProblemLongest Common Subsequence in PythonLongest Palindromic Subsequence ProblemLongest Palindromic Subsequence in PythonMinimum cost to reach the Last cell problemMinimum Cost to reach the Last Cell in 2D array using PythonNumber of Ways to reach the Last Cell with given CostNumber of Ways to reach the Last Cell with given Cost in PythonSection 32 - Dynamic ProgrammingWhat is Dynamic Programming? (Overlapping property)Where does the name of DC come from?Top Down with MemoizationBottom Up with TabulationTop Down vs Bottom UpIs Merge Sort Dynamic Programming?Number Factor Problem using Dynamic ProgrammingNumber Factor : Top Down and Bottom UpHouse Robber Problem using Dynamic ProgrammingHouse Robber : Top Down and Bottom UpConvert one string to another using Dynamic ProgrammingConvert String using Bottom UpZero One Knapsack using Dynamic ProgrammingZero One Knapsack - Top DownZero One Knapsack - Bottom UpSection 33 - CHALLENGING Dynamic Programming ProblemsLongest repeated Subsequence Length problemLongest Common Subsequence Length problemLongest Common Subsequence problemDiff UtilityShortest Common Subsequence problemLength of Longest Palindromic SubsequenceSubset Sum ProblemEgg Dropping PuzzleMaximum Length Chain of PairsSection 34 - A Recipe for Problem SolvingIntroductionStep 1 - Understand the problemStep 2 - ExamplesStep 3 - Break it DownStep 4 - Solve or SimplifyStep 5 - Look Back and Refactor
Anybody interested in learning more about data structures and algorithms or the technical interview process!,Self-taught programmers who have a basic knowledge in Python and want to be professional in Data Structure and Algorithm and begin interviewing in tech positions!,Students currently studying computer science and want supplementary material on Data Structure and Algorithm and interview preparation for after graduation!,Professional programmers who need practice for upcoming coding interviews.
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