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Data Structures & Algorithms (DSA) training By the world Record Holder Mr. Vimal Daga - Jan 2024
Data Structures & Algorithms training By the world Record Holder Mr. Vimal Daga
1.Problem-Solving Approaches | Concepts Of Algorithms | Pseudo Code | Need Of Programming Languages | Program Code & Statement | Algo-Thinking Phenomenon | Primary Goal-Solve & Approach | Constraints(Optimal-Time) | Searching Problem Concepts | Program File | Importance Of RAM & CPU (100:49)
Summary - Session-1
2.Process & Execute | Use Of RAM & CPU | Compute Devices | OOM Error Concepts | Space Complexity | Frequency Concept | Clock Speed Of CPU | Moore's Law Concept | Time Complexity | Optimization Concept | Computational Complexity | Instructions /Statements | Loop Concept | Pseudo Code (115:10)
Summary - Session-2
3.Time & Space Complexity | Asymptotic Analysis | Big-O Notation | For Loop() | Constant Time | O(1) & O(n)Algorithm Concepts | Algorithmic Analysis Thinking | O(n) Linear Time | Functions (101:44)
Summary - Session-3
4. recursion function | discrete numbers | types of complexity | if else condition | types of loops | for loop | while loop | Bottom top up concept | universe patterns | depth exceeded concept | recursion error | design algorithm (115:37)
Summary - Session-4
5. Loops- Iteration & Recursion | Recursion-Func() Loop | Recursion Concept | Direct & Indirect Recursion | Base/Stop Cases | Tail & Non-Tail Recursion | Precedence/Order Concept | Stack Frames / Activation Records | LIFO Mechanism | Stack Function | Limitations Of Stack Memory (120:29)
Summary - Session 5
5.1 Revision session (60:40)
6. Concept Of Optimized Algorithm | Stack Memory & Computational Complexity | BigO Importance Recursion Relation | Difference b/w Recursion & Iteration | Problem Statment & Possible Solutions | Factorial With Eg. | Tail & Non-Tail Recursion | Stack Frames | Linear Time | (91:55)
Summary - Session 6
7. TCO | space complexity | time complexity | stack overflow | iteration | recursion | devlopment time | compiler | source code | compile time | executable code | interpreter language | tail recursion | tail call optimization | Depth recursion error | tail_recursion module (91:21)
Summary - Session 7
7.1 Revision session (78:15)
8. Prediction of Pattern in Series | Fibonacci Series | Recursion Relation | Practical Of Fibonacci Series | Base & Stop Case | ProcessEXP Program | Recursion-Tree | activation record | recursion call | stack frame | space complexity | time complexity | febbonocci series | (106:25)
Summary - Session 8
9. Big-O Notation | Time Complexity | P & NP Class Problem | O(N) & O(2^N) | Difference B/w Recursion & Iteration | Convert NP Into P problem | Fibonacci Series | Solved Space & Time Complexity | Fibonacci Series (64:58)
Summary - Session 9
10. TCO | Loop-iteration & for | Time & Space Complexity of Different Alg. | Big-O(1) Concept | Tail Recursion | Performance Tuning | Sum of N natural No. Problem | Right way to Use Programming languages | Syntax Of C/C++ & Python (64:17)
Summary - Session 10
11. Searching Algorithms | Variables | Time Complexity | Linear Search Algorithm | Array- Data Items | For Loop | Hash Tables Introduction | Best & Worst Case Scenario | Constant Time Complexity | Multi- Occurrence (94:11)
Summary - Session 11
12. Linear Search | Binary Search Algorithm | Best & Worst Case Scenario | Searching By Half | Difference B/w Binary & Linear Search | log Concept | Sorted & Unsorted Data | Sorting Algorithm | Binary Search In Python (107:30)
Summay - Session 12
13. Data Manipulation Concepts | Sorting Algorithms Eg-Quick, Merge & Bubble Etc. | Importance Of Sorting Algorithms | Time Complexities of Algorithms | Working Principle -Bubble Sort Alg. | Nested For Loop & Swapping | Bubble Sort Alg. Using python (121:55)
Summary - Session 13
13.1_ Data Structures & Algorithms training By the world Record Holder Mr. Vimal Daga on 8th Mar. 24 _GMT20240308-132519 (61:32)
14. Real-Time Sorting | Short Keys | Insertion Sorting | Real Industry Use-cases | Insertion Sorting Using Python | Insert Function | Worst-case Scenario | Time Complexity (103:35)
Summary - Session14
15. Quick sort algorithm | Partitioning | Divide and conquer method | Pivot | Myth about pivot | Subset array | Time complexity of quick sort (98:44)
Summary - Session 15
16 "Partition exchange | Logic for quick sort | Code for quick sort | Recursion | Swapping " (101:27)
Summary - Session 16
17. " Approach to design an algorithm | Divide and conquer approach | Importance of finding patterns | Stop cases | Multi provisioning | Dividing bigger problem into sub problems | Bottom up approach | Recursion | Min and max problem " (84:38)
Summary Session 17
18. Comparison algorithm approach | Dividing bigger problems into sub problems | Bottom up approach | Recursion | Solving min-max problem using the divide and conquer approach | Writing code for the min-max proble (103:34)
Summary Session 18
19. Optimization | Greedy Algorithm | Job Sequencing with deadline Problem. | Optimal Solution | Real world examples that can be solved by greedy algo | Sequencing (80:34)
Summary Session 19
Important Links
Drive Link
Discord Link
LinkedIn Community Link
Extra Sessions
Session 1 - "STL (Standard Template Library) |Time Complexity | Extend Array | Append Data | CPU Time | POP | Vector | Capacity Function | push_back | Size Function (116:21)
Session 2 - Create dynamic array | Vector | Traversal Operation | Iterator Class | push_back keyword | itr object | foreach loop | Challenges in array (102:50)
Session 3 - Limitation of Array| OutOfMemory Exception | Continuous way | Non-continuous way | Linked List | Node | Self-referencing class (131:59)
Session 4 - Linked List | Head Node| Last Node | Create Node | Updating Memory Address of a node | Linked List Variables | Insertion Operation in linked list | Traverse into linked list using loop (112:45)
Session 5 - Create Linked List Using Constructor | Read Operation | Length Operation | Abstract Data Type(ADT)| Destructor | Delete Linked List Using Destructo (118:28)
Session 6 - Insertion Operation on Array | Time Complexity of Insertion Operation on Array | Insertion Operation on Linked List | Time Complexity (Best Case Scenario) of Insertion Operation on Linked List | Time Complexity (Worst Case Scenario) of Insertion Operation on Linked List (106:34)
Session 7 - LINKED LIST | GET | SET | UPDATE | ARROW OPERATOR | ITERATION | CONSTRUCTOR | DESTRUCTOR | ACCESSING THE DATA | Best Case and Worst Case scenarios | Head node | Tail node (103:38)
Session 8 - Singly linked list using STL | forward_list library | Doubly Linked List | Create Node in Doubly Linked List (80:11)
Session 9 - Create Doubly Linked List | Insert Operation | Forward Display Operation | Reverse Display Operation | isEmpty method (104:47)
Session 10 - push back operation | push front operation | Time complexity of push back & front method | peek operation | Time complexity of peek operation | pop operation | Time complexity of pop operation (114:28)
Session 11 - FIFO(First In First Out) | Queue Data Structure | Push Operation in Queue | Pop Operation in Queue (63:50)
Session 12 - Queue : Using Doubly Linked List | Enqueue | Time Complexity of enqueue method | Dequeue | Time Complexity of dequeue method | Display Method | Time Complexity of display method | isEmpty method | Time Complexity of isEmpty method (95:48)
Session 13 -stack data structures|Time complexity | space complexity |queue |array|list|pop operation|puch back |pop back |activation record |LIFO| (97:02)
Session 14 - Basics about Tree | Data structure | Terminologies used in Tree Data Structure such as (Leaf, root, sibling, etc) | Ancestor and Descendants | Implement a Tree DS | Binary Search Tree(BST) (132:47)
Session 15 - linear and nonlinear (difference, example) | Travers Binary Tree | Difference between Depth first traversal and Breadth first traversal | Traverse using pre-order (130:02)
Session 16 - Strict binary tree | Space and time complexity of pre-order & in-order traversal | In-order & post-order traversal (114:57)
11. Searching Algorithms | Variables | Time Complexity | Linear Search Algorithm | Array- Data Items | For Loop | Hash Tables Introduction | Best & Worst Case Scenario | Constant Time Complexity | Multi- Occurrence
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