Published 3/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 20.5 GB | Duration: 16h 22m
One Stop Learning destination for Data Structure students
What you’ll learn
SPPU Computer branch students who wanted to score good marks in exam without wasting time in searching concepts on internet
Third year and FInal year students to preparing for placement (As data structure plays important role in placement)
Students preparing for GATE to understand data structure concept in detail
Anyone who wants to professional programming (Data structure is a heart of programming)
Requirements
All prerequisite videos are available for this course for free
Description
Hi,Data Structure is a heart of programming, That’s why all product development company focus on data structure and in almost all technical interview data structure plays very important role.In this course we will start with prerequisite of data structure and then slowly we will move from basic to advance level data structure.This Course is Mapped to SPPU 2019 Pattern Syllabus. Every Data structures is explained thoroughly concerning following points: ConceptsExamples Algorithms Logic CodesAnalysisThis course will be helpful throughout you programming journey, even after you placed in good company.This course covers each topic in greater details, every topic is covered on Whiteboard which will improve your Problem Solving and Analytical Skills. Every Data Structure is discussed, analyzed and implemented with a Practical line-by-line coding.Many developers who are “self taught”, feel that one of the main disadvantages they face compared to college educated graduates in computer science is the fact that they don’t have knowledge about algorithms, data structures and the notorious Big-O Notation. Get on the same level as someone with computer science degree by learning the fundamental building blocks of computer science which will give you a big boost during interviews. What Will You Get ?To study data structures and their implementations and applications.To learn different searching and sorting techniques.To study some advanced data structures such as stack, Queue, Trees, Graphs, Tables, etc.To learn algorithm development and analysis of algorithms.On completion of the course, you will be able to–Perform basic analysis of algorithms with respect to time and space complexity.Select appropriate searching and/or sorting techniques in the application development.Implement abstract data type (ADT) and data structures for given application.Apply implement learned algorithm design techniques and data structures to solve problems.Design different hashing functions
Overview
Section 1: Free Prerequisite Videos to understand C++ programming.
Lecture 1 Variables Concept
Lecture 2 Varable-Facts
Lecture 3 How to take input in C++
Lecture 4 Interesting Facts and Common Errors while taking Input in C++
Lecture 5 Operators in C++
Lecture 6 If-Else concept in C++ (Conditional Decision Control Statement)
Lecture 7 Interesting Facts and Important Things to Know about If- else
Lecture 8 If else Practice Problems
Lecture 9 Loops Concepts and its Use in C++
Lecture 10 Loops Practice Problems
Lecture 11 Nested Loops in C++
Lecture 12 Switch Case in C++
Lecture 13 Introduction to Functions
Lecture 14 Function with Reference variable C++
Lecture 15 Class Concept in C++
Section 2: Course Introduction
Lecture 16 Course overview
Section 3: Unit 1 – Introduction to Algorithm and Data Structures
Lecture 17 Algorithms Introduction
Lecture 18 Asymptotic Notations
Lecture 19 Step Count Method
Lecture 20 Programming Constructs
Lecture 21 Types of Data Structures
Section 4: Unit 2: Arrays
Lecture 22 Introduction
Lecture 23 Array as an ADT
Lecture 24 Multi dimentional Arrays
Lecture 25 Address Calculation
Section 5: Unit – 2 Single Variable Polynomial
Lecture 26 Introduction
Lecture 27 Polynomial Addition
Lecture 28 Polynomial Multiplication
Section 6: Unit 2 – Sparse Matrix
Lecture 29 Introduction
Lecture 30 Simple transpose
Lecture 31 Fast transpose
Lecture 32 Sparse Matrix Addition – Theopry and examples
Lecture 33 Sparse Matrix Addition – Code
Lecture 34 Sparse Matrix Fast Transpose Code
Section 7: Unit 3 – Searching
Lecture 35 Linear Search
Lecture 36 Sentinel Search
Lecture 37 Binary Search
Lecture 38 Index Sequential Search – Theory and examples
Lecture 39 Index Sequential Search – Code and Analysis
Lecture 40 Fibonnaci Search
Section 8: Unit 3 Prerequisite (Recursion)
Lecture 41 Recursion Introduction
Section 9: Unit 3 – Sorting
Lecture 42 Bubble sort – Theory and Examples
Lecture 43 Bubble Sort Code and Analysis
Lecture 44 Selection Sort – Theory and Examples
Lecture 45 Selection Sort – Code and Analysis
Lecture 46 Insertion Sort – Theory and Examples
Lecture 47 Insertion Sort – Code and Analysis
Lecture 48 Quick Sort – Theory and Examples
Lecture 49 Quick Sort – Code and Analysis
Lecture 50 Merge Sort – Theory and Examples
Lecture 51 Merge Sort – Code and Analysis
Lecture 52 Shell Sort
Lecture 53 Bucket Sort
Lecture 54 Radix Sort
Lecture 55 Counting Sort
Section 10: UNIT 4 Pointers (Pre-requisite)
Lecture 56 Pointers – Part 1
Lecture 57 Pointers part 2
Section 11: Unit 4 – Linked List
Lecture 58 Singly Linked List – Creation and display
Lecture 59 Singly Link List – Insertion
Lecture 60 Singly Linked List – Seach and Update
Lecture 61 SLL – Deletion
Lecture 62 Doubly Linked List – Create and Display
Lecture 63 Doubly Linked List – insertion and deletion
Lecture 64 Circular Linked List
Section 12: Unit 5 – Stack
Lecture 65 Stack implementation using Arrays
Lecture 66 Stack implementation using Linked List
Lecture 67 Stack ADT – Practical way
Lecture 68 Expression conversions using stack
Lecture 69 Expression evaluation using stack
Section 13: Unit 6 – Queue
Lecture 70 Queue Implementation using Array
Lecture 71 Queue Implementation using Linked List
Lecture 72 Circular Queue
Lecture 73 DeQueue – Double Ended Queue
Lecture 74 Priority Queue
This Course is Mapped to SPPU 2019 Pattern Syllabus. Every Data structures is explained thoroughly concerning following points:,1. Concept,2. Examples,3. Algorithm,4. Logic,5. Code,6. Analysis
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