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Programming, Data Structures and Algorithms (GATE DA)
For Correct, Clear & Complete Understanding. "GO" for the Best.
| star star star star star | 5.0 (7 ratings) |
Instructor: Sachin Mittal (MTech IISc Bangalore, Ex-Amazon Scientist, GATE AIR 33)
Language: English
Validity Period: 180 days
Validity Period: 365 days
₹5000 20% OFF
₹3999 including 18% GST
₹7000 28% OFF
₹4999 including 18% GST
"Programming, Data Structures and Algorithms" Syllabus Covered:
Programming in Python, basic data structures: stacks, queues, linked lists, trees, hash tables; Search algorithms: linear search and binary search, basic sorting algorithms: selection sort, bubble sort and insertion sort; divide and conquer: mergesort, quicksort; introduction to graph theory; basic graph algorithms: traversals and shortest path.
Features of the course:
One-Stop Solution for your Complete DBMS Preparation!!
1. Quality Content: No Rote-learning. No poor understanding. No rote memorization of formulas/tables/theorems/results. Understand everything with proof, intuition, and ideas.
2. No Prerequisites: Every concept is taught from the basics, without assuming any prior knowledge whatsoever.
3. Homeworks, Quizzes, DPPs & Practice Sets: Practice questions that progressively build your ability to apply concepts to unfamiliar problems.
4. GATE PYQs Video Solutions: Detailed Video Solutions of GATE Previous Years' Questions, with Complete Analysis of each question. Analyze GATE questions to understand exactly how concepts are tested and what kind of thinking is required.
5. Weekly Quizzes: We provide many weekly quizzes to evaluate your understanding of concepts. Quizzes are available to attempt anytime.
(NOTE: Quizzes are freely accessible to students enrolled in our GATE DA Complete Course. Students who are not enrolled in GATE DA Complete Course can enroll for Quizzes HERE.)
6. Doubt Resolution: Have a doubt while studying? Just ask us. All your doubts are resolved directly by our faculty and team of experts. We have a dedicated Private Telegram Group for enrolled students, where you can post your doubts and get them clarified by our faculty. You don’t need to look elsewhere for solutions or explanations. We’re there to help you whenever you get stuck.
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| Python Programming | |||
| Lecture 1: Introduction to Python Programming and Variables in Python | |||
| Annotated Notes Lecture 1 Introduction to Python (59 pages) | |||
| Lecture 2: Operators and Conditional Statements in Python | |||
| Annotated Notes Lecture 2 Operators and Conditional Statements in Python (110 pages) | |||
| Lecture 3: Strings in Python | |||
| Annotated Notes Lecture 3 Strings in Python (90 pages) | |||
| Lecture 4: Lists in Python | |||
| Annotated Notes Lecture 4 Lists in Python (94 pages) | |||
| Lecture 5: Loops and List Comprehension in Python | |||
| Annotated Notes Lecture 5 Loops and List Comprehension in Python (119 pages) | |||
| Lecture 6: References, Objects, and List aliasing in Python | |||
| Annotated Notes Lecture 6 References and Objects in Python (77 pages) | |||
| Lecture 7: Functions in Python | |||
| Annotated Notes Lecture 7 Functions in Python (69 pages) | |||
| Lecture 8: More on Functions in Python | |||
| Annotated Notes Lecture 8 More on Functions in Python (51 pages) | |||
| Lecture 9: Default, Keyword, and Variable Number of Arguments | Tuples in Python | |||
| Annotated Notes Lecture 9 Default, Keyword, and Variable Number of Arguments | Tuples in Python (83 pages) | |||
| Lecture 10: Zip Function, and Lambda Functions | |||
| Annotated Notes Lecture 10 Zip and Lambda Functions (82 pages) | |||
| Lecture 11: Dictionary and Sets in Python | |||
| Annotated Notes Lecture 11 Dictionary (70 pages) | |||
| Lecture 12: Sets In python | |||
| Annotated Notes Lecture 12 - Sets (33 pages) | |||
| Lecture 13: OOPS Concepts | |||
| Annotated Notes Lecture 13 OOPS Concepts (62 pages) | |||
| Lecture 14: Linked List | |||
| Annotated Notes Lecture 14 : LinkedList oops contd (47 pages) | |||
| Lecture 15: Linked List - Insertion Deletion | |||
| Annotated Notes Lecture 15 : Linked List Insertion Deletion (23 pages) | |||
| Lecture 16 : Introduction to Recursion 95:00 | |||
| Annotated Notes Lecture 16 : Introduction to Recursion (56 pages) | |||
| First Lecture on Python Object Oriented Programming | |||
| Annotated Notes First Lecture on Python Object Oriented Programming (109 pages) | |||
| Linked List (NEW) | |||
| Lecture 1A. Introduction to Linked list 46:00 | |||
| Lecture 1B. More Operations on Linked list 23:00 | |||
| Annotated Notes Lecture 1 Linked List (76 pages) | |||
| Lecture 2A. Introduction to Recursion 22:00 | |||
| Lecture 2B. First Two Questions and Two Variations on Recursion 25:00 | |||
| Lecture 2C. More Questions on Recursion 32:00 | |||
| Lecture 3A. Recursion in LL 29:00 | |||
| Lecture 3B. Tricky and Nice Questions on Linked List Recursion 65:00 | |||
| Annotated Notes Lecture 2 and 3 Recursion in LL (99 pages) | |||
| Lecture 4A. Circular Linked List 30:00 | |||
| Lecture 4B. Doubly Linked List 34:00 | |||
| Annotated Notes Lecture 4 Circular and Doubly LL (69 pages) | |||
| Practice Questions - Linked List - PYTHON (54 pages) | |||
| Linked List (Old) | |||
| Important Node | |||
| 1a. Introduction to Data Structures 3:00 | |||
| 1b. Introduction to Linked list 31:00 | |||
| 1c. Why we need Linked list | Array vs Linked list 25:00 | |||
| 1d. Printing and Finding Length of Linked List 12:00 | |||
| Lecture 1 Annotated notes (50 pages) | |||
| 2a. Insertions in linked list 23:00 | |||
| 2b.Deletion in Linked list 19:00 | |||
| OPTIONAL : Linked list C code 4:00 | |||
| linkedList | |||
| Lecture 2 Annotated Notes (33 pages) | |||
| Lecture 3 : Recursion in Linked List (Insert, Delete, questions) | |||
| Lecture 3 : Annotated Notes - Lecture 3 : Recursion in Linked List (Insert, Delete, questions) (40 pages) | |||
| Lecture 4a: GATE 2022 Reverse a Linked List ( 2 variations ) - PYTHON | |||
| Lecture 4b: Reverse a Linked List ( Variations 3 and 4) - PYTHON | |||
| Reverse_linked_List.py | |||
| Lecture 4: Annotated notes - Reversing Linked List and 4 variations (55 pages) | |||
| Lecture 5a : Circular Linked List - PYTHON | |||
| Lecture5b : Circular Linked List - PYTHON | |||
| Circular_linked_list.py | |||
| lecture 5 : Annotated Notes - Circular Linked List - PYTHON (64 pages) | |||
| Lecture 6 : Doubly Linked List - PYTHON | |||
| Doubly_linked_list.py | |||
| Lecture 6 : Annotated Notes - Doubly Linked List - PYTHON (39 pages) | |||
| Practice Set Linked List (56 pages) | |||
| LIVE: Linked List Practice Set Discussion | |||
| LIVE Session Annotated Notes (63 pages) | |||
| Weekly Quiz 20 - Linked List (11 pages) | |||
| Practice Questions - Linked List - PYTHON (54 pages) | |||
| Asymptotic Analysis and Loop Complexities | |||
| 5a. Introduction to Asymptotic Analysis 17:00 | |||
| 5b. Big oh and Big omega Asymptotic Notations 39:00 | |||
| 5c. Theta Asymptotic notation 13:00 | |||
| 5d. What is Asymptotic comparison | how LOG works | rice grain story 31:00 | |||
| 5e. Comparing Different Functions Asymptotically 53:00 | |||
| 5f. Little Oh Little Omega | Properties of asymptotic notation | Stirling approximation 36:00 | |||
| 6a.Formal set notation of Asymptote symbols 7:00 | |||
| 6b. Asymptotic Notations GATE CSE PYQs 1994, 96, 2000,1,3,4,8,11,17 21:00 | |||
| 6c. Analysing the loops time complexity 29:00 | |||
| 6d. Time Complexity of loops -2 17:00 | |||
| Annotated Notes: Lecture 5, 6 - Asymptotic Analysis (172 pages) | |||
| Practice Set Loop Complexities (43 pages) | |||
| LIVE: Loop Time Complexity Practice Set Discussion | |||
| LIVE Session Loop Time Complexity Annotated Notes (69 pages) | |||
| 7a. Brief about Best Case, Worst Case 22:00 | |||
| 7b. More about Best Case, Worst Case 26:00 | |||
| 7c. Questions on Algorithmic notations 5:00 | |||
| Annotated Notes Lecture 7 (39 pages) | |||
| Practice Set Asymptotic Notations (83 pages) | |||
| LIVE: Asymptotic Notations Practice Set Discussion -1 | |||
| LIVE: Asymptotic Notations Practice Set Discussion-2 | |||
| LIVE Session Asymptotic Notations Annotated Notes (139 pages) | |||
| Stack and Queue | |||
| 8a. Introduction to Stack and Stack Permutations 31:00 | |||
| 8b. Implementation of Stack using Array and Linked list 31:00 | |||
| 9a. Introduction to Queue 41:00 | |||
| 9b. Implementation of Queue using Array 25:00 | |||
| 9c. Queue another Implementation using Array with F=R=0 | GATE 2012 25:00 | |||
| 9d. Implementing Queue using Linked List 11:00 | |||
| 9e. Queue using two stacks 16:00 | |||
| 10a. Stack using two queues 12:00 | |||
| 10b. Balancing parentheses and Two Stacks in one array 13:00 | |||
| 10c. Infix, Prefix & Postfix and Conversion to each other 31:00 | |||
| 10d. Infix to Postfix using Stack and Postfix evaluation using Stack 14:00 | |||
| Stack and Queue Anotated Notes (152 pages) | |||
| Practice Set Stack and Queue (46 pages) | |||
| LIVE: Stack and Queue Practice Set Discussion-1 | |||
| LIVE Stack and Queue Practice Set Discussion 2 109:00 | |||
| LIVE Session Stack and Queue Annotated Notes (102 pages) | |||
| Stacks and GATE PYQs - PYTHON | |||
| Annotated Notes : Stacks and GATE PYQs Python (57 pages) | |||
| Queues and GATE PYQs - PYTHON | |||
| Annotated Notes : Queues and GATE PYQs Python (64 pages) | |||
| Binary Trees | |||
| 11a. Introduction to Binary trees 33:00 | |||
| 11b. Some questions and representation of tree 29:00 | |||
| 11c. Questions on Binary trees 34:00 | |||
| 11d. Questions on Binary trees 2 24:00 | |||
| 12a. Binary Tree Traversals 20:00 | |||
| 12b. Binary tree construction using preorder postorder and inorder 27:00 | |||
| 12c. Binary tree construction using preorder postorder and inorder 2 21:00 | |||
| 13a. Introduction to Binary Search Tree 18:00 | |||
| 13b. Range Search in Binary Search Tree | GATE 2014 | GATE 2020 32:00 | |||
| PDF: Range Search Binary Search Tree Animations (Stanford Slides) (82 pages) | |||
| 13c. BST Deletion 21:00 | |||
| 14a. GATE 1996 Possible probe sequences 20:00 | |||
| 14b. BST PYQs 1997, 2001, 06, 07, 16 19:00 | |||
| 14c. BST Time Complexities 18:00 | |||
| Annotated Notes Binary Tree and BST (212 pages) | |||
| Practice Set Binary Trees and Binary Search Tree (73 pages) | |||
| LIVE Binary Tree and Binary Search Tree Practice Set Discussion - 1 | |||
| LIVE Binary Tree and Binary Search Tree Practice Set Discussion - 2 | |||
| LIVE SessionBinary Tree and Binary Search Tree Annotated Notes (93 pages) | |||
| Session - 1 : Binary Trees Questions & PYQs - PYTHON | |||
| Annotated Notes : Session - 1 : Binary Trees Questions & PYQs - PYTHON (38 pages) | |||
| Session - 2 : Binary Trees Questions & PYQs - PYTHON | |||
| Annotated Notes : Session - 2 : Binary Trees and PYQs - PYTHON (30 pages) | |||
| Hashing | |||
| 20a. Motivation to hashing and Direct address table 15:00 | |||
| 20b. Introduction to hashing 21:00 | |||
| 20c. Collision resolution techniques 11:00 | |||
| 20d. Avg case performance chaining 30:00 | |||
| 21a. Linear Probing 27:00 | |||
| 21 b. Quadratic probing and Double hashing 20:00 | |||
| 21c. Possible Number of probes 13:00 | |||
| 22a. [Optional but please watch ] UnSucessfull search time open addressing 36:00 | |||
| 22b. [Optional but please watch ] Successful search time open addressing 6:00 | |||
| 23 a. Probability Background (video from Probability course) Bernoulli and Binomial RVs 77:00 | |||
| 23b. Three popular expectation questions in hashing 18:00 | |||
| Hashing Anotated Notes (185 pages) | |||
| Why Study Algorithms | |||
| 1a. Why Study Algorithms 13:00 | |||
| 1b.An algorithm that changed history And Child's algorithm 9:00 | |||
| Time Complexity of Recursive Programs | |||
| 2a. Introduction to recurrence relations 15:00 | |||
| 2b. Solving recurrence using Iteration Method 9:00 | |||
| 2c. More Examples of Iteration Method 10:00 | |||
| 3a. Solving recurrence using Tree Method 24:00 | |||
| 3b. More Examples Tree Method 16:00 | |||
| 3c. Even More Examples Tree Method 5:00 | |||
| 3d. More Examples Tree Method 12:00 | |||
| 4a. Masters Theorem Idea and examples 27:00 | |||
| 4b. Examples On Master Theorem 4:00 | |||
| 4c. Proof of Master Theorem 16:00 | |||
| 5a. Generalised Master Theorem 6:00 | |||
| 5b. [Optional but watch] Extended Master Theorem 15:00 | |||
| 5c. Various Examples of Master Theorem 7:00 | |||
| 5d. Problems that master theorem can not solve 5:00 | |||
| 6a. Introduction to change to variable method 15:00 | |||
| 6b. Examples on Change of Variable 12:00 | |||
| 6c. Few more examples on change of variable method 5:00 | |||
| 6d. Some More variation 17:00 | |||
| Annotated Notes Module 1 Solving Reccurance relation (221 pages) | |||
| Divide and Conquer Algorithms (Part-1) | |||
| 7a. Introduction to Divide and Conquer Algorithm 24:00 | |||
| 7b. Maximum of an array using D and C 10:00 | |||
| 7c. Example 2- Sum of an array 5:00 | |||
| 7d. Example 3- Search in an array 6:00 | |||
| 7e. Example 4 - Dumb Sort 8:00 | |||
| A Note: Viewing Recurrence as Induction | |||
| 8a. Introduction to Merge Sort algorithm 11:00 | |||
| 8b.Heart of Merge Sort- Merge Procedure 16:00 | |||
| 8c. Merge Procedure -2 23:00 | |||
| 8d. Merge Sort Recursive tree with example 13:00 | |||
| 8e. Merge Sort Analysis (Contd..) 21:00 | |||
| 9a. Merge Sort questions -1 11:00 | |||
| 9b. Merge Sort questions -2 14:00 | |||
| 9c. More Questions on Merge sort 26:00 | |||
| 10a. Iterative (or Bottom-up) Merge sort 11:00 | |||
| 10b. GATE 1999 question on Bottom up Merge Sort 2:00 | |||
| 10c. Time Complexity of Iterative Merge sort 17:00 | |||
| 10d. [Optional and Skip] Implementation of Iterative Merge sort 13:00 | |||
| 11a. Merging k sorted arrays Part 1 22:00 | |||
| 11b. Merging k sorted arrays Part 2 22:00 | |||
| 11d. Definition of Stable and In-place sorting 17:00 | |||
| [DELETED] In Place and Space Complexity 5:00 | |||
| Annotated Notes Divide and Conquer Algorithms (Part-1) (178 pages) | |||
| Divide and Conquer - PYTHON | |||
| Annotated : Divide and Conquer - PYTHON (53 pages) | |||
| Merge Sort & Questions | |||
| Annotated : Merge Sort & Questions (42 pages) | |||
| Divide and Conquer Algorithms (Part-2) | |||
| 12a. Introduction to Quick Sort 28:00 | |||
| 12b. Working Example of Quick Sort 30:00 | |||
| 12c. Quick sort Analysis and Randomised quick sort 40:00 | |||
| 12d. GATE 2014 question 11:00 | |||
| 12e. Questions on quick sort 23:00 | |||
| 12f. [Optional and Skip] Average case analysis of quick sort 5:00 | |||
| 13a. The Select algorithm 25:00 | |||
| 13b. Binary Search 28:00 | |||
| Annotated notes Divide and Conquer part 2 (212 pages) | |||
| Quick Sort - PYTHON | |||
| Annotated : Quick Sort - PYTHON (22 pages) | |||
| Breadth First and Depth First search (BFS and DFS) | |||
| 14a. Introduction to Graphs | Adjacency List and Matrix 19:00 | |||
| 14b. intuition for graph search methods 24:00 | |||
| 14c. Introduction to DFS 23:00 | |||
| 14d. DFS Implementation (Recursive and explicit stack) and Time complexity 40:00 | |||
| 15a. DFS Parentheses Theorem | GATE 2006 | |||
| 15b. DFS Edge Classifications 27:00 | |||
| 15c. Questions on DFS Edge Classification 30:00 | |||
| 15d. [Optional] Back-edge and cycle question 18:00 | |||
| 16a. DFS Application 1- Cycles in graph 31:00 | |||
| 16b. GATE 2007 question on DAG finish time 21:00 | |||
| 16c. DFS Application 2 Topological sort | GATE 2014 19:00 | |||
| 16d. DFS Application 3 Articulation Point | GATE 2021 46:00 | |||
| 17a. Introduction to BFS 28:00 | |||
| 17b. BFS few Observations(Properties) and BFS Edge Classification 37:00 | |||
| 17c. BFS Applications 29:00 | |||
| Annotated Notes DFS BFS (302 pages) | |||
| Shortest Paths Algorithms (Greedy Algorithms) | |||
| 18a. Introduction to Greedy Algorithms | Introduction and Intuitive proof of Dijkstra 56:00 | |||
| 18b. Dijkstra code and Working Example 1 17:00 | |||
| 18c. Dijkstra Working Example 2 15:00 | |||
| 18d. Dijkstra Working Example 3 10:00 | |||
| 19a. Dijkstra on negative weights 44:00 | |||
| 19b. Video From DS Course: Priority Queues 17:00 | |||
| 19c. Dijkstra Time Complexity 33:00 | |||
| 19d. Dijkstra Time Complexity on more variant data structures | Dijkstra Demo 10:00 | |||
| 20a. DAG Shortest Path | Shortest Path in Directed Acyclic Graph 17:00 | |||
| 20b. Intuition Behind Bellman Ford Algorithm 28:00 | |||
| 20c. Examples of Bellman Ford | Time complexity 36:00 | |||
| 20d. Bellman ford proof and Early termination 23:00 | |||
| Annotated Notes Dijkstra, DAG Shortest Path Algo, and Bellman Ford (163 pages) | |||
| Sorting Algorithms (selection, insertion, bubble, counting sort) | |||
| 21a .Bubble Sort 27:00 | |||
| 21b .Insertion Sort 24:00 | |||
| 21c .Bubble Sort and Insertion Sort 34:00 | |||
| 21d. Selection Sort and Heap Sort 37:00 | |||
| 21e. Decision Tree 52:00 | |||
| 21f. [Optional] Counting Sort and Radix Sort 34:00 | |||
| Annotated Notes Sorting Algorithms (92 pages) | |||
| Bubble Sort and Selection Sort with Questions - PYTHON | |||
| Annotated Notes : Bubble Sort and Selection Sort with Questions - PYTHON (32 pages) | |||
| Insertion Sort - PYTHON | |||
| Annotated Notes : Insertion Sort - PYTHON (23 pages) | |||
| Heap & Heap-Sort - PYTHON | |||
| Annotated Notes : Heap and Heap Sort - PYTHON (30 pages) | |||
| Live Session on GATE PYQs | |||
| Session 1: PYQs on DFS BFS and Sorting 81:00 | |||
| Annotated Notes Session 1 PYQs on DFS BFS and Sorting (38 pages) | |||
| Toppers' Handwritten Notes | |||
| Detailed Notes | |||
| Short Notes | |||
| Feedback & Review | |||
| Feedback & Review | |||
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