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| Item Details | Price | ||
|---|---|---|---|
Unlock the Power of Algorithms: Master the Art of Problem Solving, Complexity Analysis, and Optimization Strategies in the Revolutionary World of Computing in 2024!
Learn, Understand, Discuss. "GO" for the Best.
| star star star star star | 5.0 (3 ratings) |
Instructor: Sachin Mittal(MTech IISc Bangalore, Ex-Amazon Scientist, GATE AIR 33)
Language: English
Valid Till: 2024-02-15
Description:
Algorithms 2024 is a comprehensive course that introduces students to the fundamental concepts and techniques of algorithms. Through a combination of theoretical lectures and practical exercises, students will gain a solid understanding of algorithms and their applications in problem-solving.
Key Highlights:
What you will learn:
Features of the course:
1. Quality Content: No Rote-learning. No poor understanding. No By-hearting of formulas, tables or theorems. Understand everything with proofs, intuitions, and ideas.
2. No Prerequisites: Every concept is taught from basics, without assuming any prior knowledge whatsoever.
3. Daily Homework: Practice material, with solutions, for Every Lecture to test your understanding of concepts of the respective lecture.
4. Summary Lectures: Short videos which summarise every concept and detail of the course. Helps in quick revision.
5. Quality Practice Sets: Practice Sets from standard resources, with solutions, containing a lot of quality questions for practice.
6. Weekly Quizzes: Every week, there will be a Live Quiz, containing 15-20 questions, to evaluate your understanding of concepts taught in the previous week. The Quiz questions can be seen and solved even after the live quiz is over.
7. Doubt Resolution: All your doubts will be resolved directly by the faculty. There is a dedicated Telegram group for Enrolled Students of Goclasses where our faculties resolve students' doubts. So, our students don't have to go anywhere else for asking doubts.
Enroll Now.
| Python Programming | |||
| Lecture 1: Introduction to Python Programming and Variables in Python | |||
| Annotated Notes Lecture 1 Introduction to Python | |||
| Lecture 2: Operators and Conditional Statements in Python | |||
| Annotated Notes Lecture 2 Operators and Conditional Statements in Python | |||
| Lecture 3: Strings in Python | |||
| Annotated Notes Lecture 3 Strings in Python | |||
| Lecture 4: Lists in Python | |||
| Annotated Notes Lecture 4 Lists in Python | |||
| Lecture 5: Loops and List Comprehension in Python | |||
| Annotated Notes Lecture 5 Loops and List Comprehension in Python | |||
| Lecture 6: References, Objects, and List aliasing in Python | |||
| Annotated Notes Lecture 6 References and Objects in Python | |||
| Lecture 7: Functions in Python | |||
| Annotated Notes Lecture 7 Functions in Python | |||
| Lecture 8: More on Functions in Python | |||
| Annotated Notes Lecture 8 More on Functions in Python | |||
| 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 | |||
| Lecture 10: Zip Function, and Lambda Functions | |||
| Annotated Notes Lecture 10 Zip and Lambda Functions | |||
| Lecture 11: Dictionary and Sets in Python | |||
| Annotated Notes Lecture 11 Dictionary | |||
| Lecture 12: Sets In python | |||
| Annotated Notes Lecture 12 - Sets | |||
| Lecture 13: OOPS Concepts | |||
| Annotated Notes Lecture 13 OOPS Concepts | |||
| Lecture 14: Linked List | |||
| Annotated Notes Lecture 14 : LinkedList oops contd | |||
| Lecture 15: Linked List - Insertion Deletion | |||
| Annotated Notes Lecture 15 : Linked List Insertion Deletion | |||
| Lecture 16 : Introduction to Recursion | |||
| Annotated Notes Lecture 16 : Introduction to Recursion | |||
| First Lecture on Python Object Oriented Programming | |||
| Annotated Notes First Lecture on Python Object Oriented Programming | |||
| Linked List in Python By Sachin Sir | |||
| Linked List | |||
| 1a. Introduction to Data Structures | |||
| 1b. Introduction to Linked list | |||
| 1c. Why we need Linked list | Array vs Linked list | |||
| 1d. Printing and Finding Length of Linked List | |||
| Lecture 1 Annotated notes | |||
| 2a. Insertions in linked list | |||
| 2b.Deletion in Linked list | |||
| OPTIONAL : Linked list C code | |||
| linkedList | |||
| Lecture 2 Annotated Notes | |||
| Lecture 3 : Recursion in Linked List (Insert, Delete, questions) | |||
| Lecture 3 : Annotated Notes - Lecture 3 : Recursion in Linked List (Insert, Delete, questions) | |||
| 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 | |||
| Lecture 5a : Circular Linked List - PYTHON | |||
| Lecture5b : Circular Linked List - PYTHON | |||
| Circular_linked_list.py | |||
| lecture 5 : Annotated Notes - Circular Linked List - PYTHON | |||
| Lecture 6 : Doubly Linked List - PYTHON | |||
| Doubly_linked_list.py | |||
| Lecture 6 : Annotated Notes - Doubly Linked List - PYTHON | |||
| Practice Set Linked List | |||
| LIVE: Linked List Practice Set Discussion | |||
| LIVE Session Annotated Notes | |||
| Weekly Quiz 20 - Linked List | |||
| Practice Questions - Linked List - PYTHON | |||
| Asymptotic Analysis and Loop Complexities | |||
| 5a. Introduction to Asymptotic Analysis | |||
| 5b. Big oh and Big omega Asymptotic Notations | |||
| 5c. Theta Asymptotic notation | |||
| 5d. What is Asymptotic comparison | how LOG works | rice grain story | |||
| 5e. Comparing Different Functions Asymptotically | |||
| 5f. Little Oh Little Omega | Properties of asymptotic notation | Stirling approximation | |||
| 6a.Formal set notation of Asymptote symbols | |||
| 6b. Asymptotic Notations GATE CSE PYQs 1994, 96, 2000,1,3,4,8,11,17 | |||
| 6c. Analysing the loops time complexity | |||
| 6d. Time Complexity of loops -2 | |||
| Annotated Notes: Lecture 5, 6 - Asymptotic Analysis | |||
| Practice Set Loop Complexities | |||
| LIVE: Loop Time Complexity Practice Set Discussion | |||
| LIVE Session Loop Time Complexity Annotated Notes | |||
| 7a. Brief about Best Case, Worst Case | |||
| 7b. More about Best Case, Worst Case | |||
| 7c. Questions on Algorithmic notations | |||
| Annotated Notes Lecture 7 | |||
| Practice Set Asymptotic Notations | |||
| LIVE: Asymptotic Notations Practice Set Discussion -1 | |||
| LIVE: Asymptotic Notations Practice Set Discussion-2 | |||
| LIVE Session Asymptotic Notations Annotated Notes | |||
| Stack and Queue | |||
| 8a. Introduction to Stack and Stack Permutations | |||
| 8b. Implementation of Stack using Array and Linked list | |||
| 9a. Introduction to Queue | |||
| 9b. Implementation of Queue using Array | |||
| 9c. Queue another Implementation using Array with F=R=0 | GATE 2012 | |||
| 9d. Implementing Queue using Linked List | |||
| 9e. Queue using two stacks | |||
| 10a. Stack using two queues | |||
| 10b. Balancing parentheses and Two Stacks in one array | |||
| 10c. Infix, Prefix & Postfix and Conversion to each other | |||
| 10d. Infix to Postfix using Stack and Postfix evaluation using Stack | |||
| Stack and Queue Anotated Notes | |||
| Practice Set Stack and Queue | |||
| LIVE: Stack and Queue Practice Set Discussion-1 | |||
| LIVE Stack and Queue Practice Set Discussion 2 | |||
| LIVE Session Stack and Queue Annotated Notes | |||
| Stacks and GATE PYQs - PYTHON | |||
| Annotated Notes : Stacks and GATE PYQs Python | |||
| Queues and GATE PYQs - PYTHON | |||
| Annotated Notes : Queues and GATE PYQs Python | |||
| Binary Trees | |||
| 11a. Introduction to Binary trees | |||
| 11b. Some questions and representation of tree | |||
| 11c. Questions on Binary trees | |||
| 11d. Questions on Binary trees 2 | |||
| 12a. Binary Tree Traversals | |||
| 12b. Binary tree construction using preorder postorder and inorder | |||
| 12c. Binary tree construction using preorder postorder and inorder 2 | |||
| 13a. Introduction to Binary Search Tree | |||
| 13b. Range Search in Binary Search Tree | GATE 2014 | GATE 2020 | |||
| PDF: Range Search Binary Search Tree Animations (Stanford Slides) | |||
| 13c. BST Deletion | |||
| 14a. GATE 1996 Possible probe sequences | |||
| 14b. BST PYQs 1997, 2001, 06, 07, 16 | |||
| 14c. BST Time Complexities | |||
| Annotated Notes Binary Tree and BST | |||
| Practice Set Binary Trees and Binary Search Tree | |||
| 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 | |||
| Session - 1 : Binary Trees Questions & PYQs - PYTHON | |||
| Annotated Notes : Session - 1 : Binary Trees Questions & PYQs - PYTHON | |||
| Session - 2 : Binary Trees Questions & PYQs - PYTHON | |||
| Annotated Notes : Session - 2 : Binary Trees and PYQs - PYTHON | |||
| Hashing | |||
| 20a. Motivation to hashing and Direct address table | |||
| 20b. Introduction to hashing | |||
| 20c. Collision resolution techniques | |||
| 20d. Avg case performance chaining | |||
| 21a. Linear Probing | |||
| 21 b. Quadratic probing and Double hashing | |||
| 21c. Possible Number of probes | |||
| 22a. [Optional but please watch ] UnSucessfull search time open addressing | |||
| 22b. [Optional but please watch ] Successful search time open addressing | |||
| 23 a. Probability Background (video from Probability course) Bernoulli and Binomial RVs | |||
| 23b. Three popular expectation questions in hashing | |||
| Hashing Anotated Notes | |||
| Why Study Algorithms | |||
| 1a. Why Study Algorithms | |||
| 1b.An algorithm that changed history And Child's algorithm | |||
| Time Complexity of Recursive Programs | |||
| 2a. Introduction to recurrence relations | |||
| 2b. Solving recurrence using Iteration Method | |||
| 2c. More Examples of Iteration Method | |||
| 3a. Solving recurrence using Tree Method | |||
| 3b. More Examples Tree Method | |||
| 3c. Even More Examples Tree Method | |||
| 3d. More Examples Tree Method | |||
| 4a. Masters Theorem Idea and examples | |||
| 4b. Examples On Master Theorem | |||
| 4c. Proof of Master Theorem | |||
| 5a. Generalised Master Theorem | |||
| 5b. [Optional but watch] Extended Master Theorem | |||
| 5c. Various Examples of Master Theorem | |||
| 5d. Problems that master theorem can not solve | |||
| 6a. Introduction to change to variable method | |||
| 6b. Examples on Change of Variable | |||
| 6c. Few more examples on change of variable method | |||
| 6d. Some More variation | |||
| Annotated Notes Module 1 Solving Reccurance relation | |||
| Divide and Conquer Algorithms (Part-1) | |||
| 7a. Introduction to Divide and Conquer Algorithm | |||
| 7b. Maximum of an array using D and C | |||
| 7c. Example 2- Sum of an array | |||
| 7d. Example 3- Search in an array | |||
| 7e. Example 4 - Dumb Sort | |||
| A Note: Viewing Recurrence as Induction | |||
| 8a. Introduction to Merge Sort algorithm | |||
| 8b.Heart of Merge Sort- Merge Procedure | |||
| 8c. Merge Procedure -2 | |||
| 8d. Merge Sort Recursive tree with example | |||
| 8e. Merge Sort Analysis (Contd..) | |||
| 9a. Merge Sort questions -1 | |||
| 9b. Merge Sort questions -2 | |||
| 9c. More Questions on Merge sort | |||
| 10a. Iterative (or Bottom-up) Merge sort | |||
| 10b. GATE 1999 question on Bottom up Merge Sort | |||
| 10c. Time Complexity of Iterative Merge sort | |||
| 10d. [Optional and Skip] Implementation of Iterative Merge sort | |||
| 11a. Merging k sorted arrays Part 1 | |||
| 11b. Merging k sorted arrays Part 2 | |||
| 11d. Definition of Stable and In-place sorting | |||
| [DELETED] In Place and Space Complexity | |||
| Annotated Notes Divide and Conquer Algorithms (Part-1) | |||
| Divide and Conquer - PYTHON | |||
| Annotated : Divide and Conquer - PYTHON | |||
| Merge Sort & Questions | |||
| Annotated : Merge Sort & Questions | |||
| Divide and Conquer Algorithms (Part-2) | |||
| 12a. Introduction to Quick Sort | |||
| 12b. Working Example of Quick Sort | |||
| 12c. Quick sort Analysis and Randomised quick sort | |||
| 12d. GATE 2014 question | |||
| 12e. Questions on quick sort | |||
| 12f. [Optional and Skip] Average case analysis of quick sort | |||
| 13a. The Select algorithm | |||
| 13b. Binary Search | |||
| Annotated notes Divide and Conquer part 2 | |||
| Quick Sort - PYTHON | |||
| Annotated : Quick Sort - PYTHON | |||
| Breadth First and Depth First search (BFS and DFS) | |||
| 14a. Introduction to Graphs | Adjacency List and Matrix | |||
| 14b. intuition for graph search methods | |||
| 14c. Introduction to DFS | |||
| 14d. DFS Implementation (Recursive and explicit stack) and Time complexity | |||
| 15a. DFS Parentheses Theorem | GATE 2006 | |||
| 15b. DFS Edge Classifications | |||
| 15c. Questions on DFS Edge Classification | |||
| 15d. [Optional] Back-edge and cycle question | |||
| 16a. DFS Application 1- Cycles in graph | |||
| 16b. GATE 2007 question on DAG finish time | |||
| 16c. DFS Application 2 Topological sort | GATE 2014 | |||
| 16d. DFS Application 3 Articulation Point | GATE 2021 | |||
| 17a. Introduction to BFS | |||
| 17b. BFS few Observations(Properties) and BFS Edge Classification | |||
| 17c. BFS Applications | |||
| Annotated Notes DFS BFS | |||
| Shortest Paths Algorithms (Greedy Algorithms) | |||
| 18a. Introduction to Greedy Algorithms | Introduction and Intuitive proof of Dijkstra | |||
| 18b. Dijkstra code and Working Example 1 | |||
| 18c. Dijkstra Working Example 2 | |||
| 18d. Dijkstra Working Example 3 | |||
| 19a. Dijkstra on negative weights | |||
| 19b. Video From DS Course: Priority Queues | |||
| 19c. Dijkstra Time Complexity | |||
| 19d. Dijkstra Time Complexity on more variant data structures | Dijkstra Demo | |||
| 20a. DAG Shortest Path | Shortest Path in Directed Acyclic Graph | |||
| 20b. Intuition Behind Bellman Ford Algorithm | |||
| 20c. Examples of Bellman Ford | Time complexity | |||
| 20d. Bellman ford proof and Early termination | |||
| Annotated Notes Dijkstra, DAG Shortest Path Algo, and Bellman Ford | |||
| Sorting Algorithms (selection, insertion, bubble, counting sort) | |||
| 21a .Bubble Sort | |||
| 21b .Insertion Sort | |||
| 21c .Bubble Sort and Insertion Sort | |||
| 21d. Selection Sort and Heap Sort | |||
| 21e. Decision Tree | |||
| 21f. [Optional] Counting Sort and Radix Sort | |||
| Annotated Notes Sorting Algorithms | |||
| Bubble Sort and Selection Sort with Questions - PYTHON | |||
| Annotated Notes : Bubble Sort and Selection Sort with Questions - PYTHON | |||
| Insertion Sort - PYTHON | |||
| Annotated Notes : Insertion Sort - PYTHON | |||
| Heap & Heap-Sort - PYTHON | |||
| Annotated Notes : Heap and Heap Sort - PYTHON | |||
| Student Notes | |||
| Algorithm GATE DA Student Written Notes | |||
| Data Structures GATE DA Student Written Notes | |||
| Live Session on GATE PYQs | |||
| Session 1: PYQs on DFS BFS and Sorting | |||
| Annotated Notes Session 1 PYQs on DFS BFS and Sorting | |||
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