Mastering Data Structures Building Blocks For Efficient Code

Posted By: ELK1nG

Mastering Data Structures Building Blocks For Efficient Code
Published 3/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.58 GB | Duration: 6h 55m

Data Structures Unleashed: Navigating the World of Organized Information for Efficient Programming

What you'll learn

Fundamental Understanding: Develop a strong foundation in the fundamental concepts of data structures, including arrays, linked lists, stacks, queues, and trees

Algorithmic Analysis: Learn to analyze the time and space complexity of algorithms associated with various data structures

Implementation Skills: Gain hands-on experience in implementing and manipulating data structures.

Problem-Solving Abilities: Enhance your problem-solving skills by applying data structures to solve real-world problems.

Optimization Techniques: Explore optimization strategies for data structures to achieve better performance.

Requirements

Programming Proficiency: A solid understanding of at least one programming language is crucial.

Introduction to Computer Science: Familiarity with basic computer science concepts is important.

Basic Mathematics: A foundational understanding of basic mathematical concepts, such as algebra, is often helpful for analyzing and understanding algorithms.

Logic and Problem-Solving Skills: Strong logical reasoning and problem-solving skills are essential.

Description

Embark on a journey through the intricacies of data structures with our comprehensive course, "Data Structures Unleashed." Whether you're a budding computer science student, a seasoned software engineer, or an aspiring coder, this course is designed to empower you with the knowledge and skills needed to make informed decisions about data organization in your programs.Course Highlights:1. Foundational Understanding: Delve into the core concepts of data structures, covering arrays, linked lists, stacks, queues, trees, and graphs. Gain a deep understanding of their properties, operations, and practical applications.2. Algorithmic Analysis: Learn to analyze the time and space complexity of algorithms associated with various data structures. Understand how to make informed choices based on the nature of the problem and the efficiency requirements.3. Hands-On Implementation: Translate theory into practice through hands-on coding exercises. Develop proficiency in implementing and manipulating data structures, reinforcing your understanding through practical application.4. Problem-Solving Mastery: Elevate your problem-solving skills by applying data structures to solve real-world challenges. Learn to choose the most suitable data structure for a given problem, enhancing your ability to craft efficient and effective solutions.5. Optimization Strategies: Explore optimization techniques for data structures to enhance performance. Understand how to design data structures that minimize time and space complexity, and optimize existing code for efficiency.6. Interactive Learning: Engage in a dynamic learning environment with interactive quizzes, collaborative projects, and a supportive community. Receive personalized feedback to enhance your coding and problem-solving skills.By the end of this course, you'll not only possess a comprehensive understanding of various data structures but also the confidence to implement them effectively in your programming projects. Join us on a transformative journey to unleash the power of data structures and elevate your programming capabilities to new heights. Enroll now and become a master of organized information in the world of efficient programming!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Categories

Lecture 3 Operation

Lecture 4 Memory

Lecture 5 Complexity

Lecture 6 Efficiency

Lecture 7 Types

Section 2: Array

Lecture 8 Introduction

Lecture 9 Pros & Cons

Lecture 10 Analysis

Lecture 11 Coding: Array Insert

Lecture 12 Coding: Array Access

Lecture 13 Coding: Array Update

Lecture 14 Coding: Array Delete

Lecture 15 Coding: Array Search

Lecture 16 Two Dimensional Array

Lecture 17 Three Dimensional Array

Lecture 18 Coding: Array Matrix

Lecture 19 Coding: Matrix Access

Section 3: Linked List

Lecture 20 Introduction

Lecture 21 Pros & Cons

Lecture 22 Types

Lecture 23 Coding: Single Linked List

Lecture 24 Delete a node

Lecture 25 Insert At The front

Lecture 26 Insert At The End

Lecture 27 Insert After a Node

Section 4: Linked List Operations

Lecture 28 Coding: Create

Lecture 29 Coding: Insert Front

Lecture 30 Coding: Insert At The End

Lecture 31 Coding: Insert After a Node

Lecture 32 Coding: Delete a Node

Lecture 33 Coding: Display

Lecture 34 Coding: Operation

Section 5: Stack

Lecture 35 Introduction

Lecture 36 Operations

Lecture 37 Coding: Part 01

Lecture 38 Coding: Part 02

Section 6: Queue

Lecture 39 Introduction

Lecture 40 Tips

Lecture 41 Coding: Queue using Array

Lecture 42 Coding: Queue Using Array – Empty

Lecture 43 Coding: Queue using Array – Full

Lecture 44 Coding: Queue Using Array – Enqueue

Lecture 45 Coding: Queue Using Array – Dequeue

Lecture 46 Coding: Queue Using Array – Peek

Lecture 47 Coding: Queue Using Array – Display

Lecture 48 Coding: Queue Using Array – Operation

Section 7: Queue Using Linked List

Lecture 49 Coding: Setup Node

Lecture 50 Coding: Setup Queue

Lecture 51 Coding: isEmpty

Lecture 52 Coding: Enqueue

Lecture 53 Coding: Dequeue

Lecture 54 Coding: Peek

Lecture 55 Coding: Display

Lecture 56 Coding: Operation

Section 8: Tree

Lecture 57 Introduction

Lecture 58 Binary Tree

Lecture 59 Types of Binary Tree

Lecture 60 Binary Tree Representation

Lecture 61 Binary Tree – Array Representation

Lecture 62 Coding: Array Representation

Lecture 63 Linked Structure Representation

Lecture 64 Coding: Linked Structure Represenation

Section 9: Binary Search Tree

Lecture 65 Introduction

Lecture 66 BST – Operations

Lecture 67 Coding: BST

Lecture 68 Traversal

Lecture 69 Preorder

Lecture 70 Inorder

Lecture 71 Postorder

Lecture 72 Coding: Traversal

Section 10: Graphs

Lecture 73 Introduction

Lecture 74 Terminology

Lecture 75 Cyclic And Acyclic Graphs

Lecture 76 Adjacency Matrix

Lecture 77 Coding: Adjacency Matrix

Lecture 78 Adjacency List

Lecture 79 Coding: Adjacency List

Lecture 80 Traversal

Lecture 81 DFS – Algorithm

Lecture 82 BFS – Algorithm

Computer Science Students: Both undergraduate and graduate students pursuing a degree in computer science or a related field will benefit from a data structures course as it forms a fundamental part of their curriculum.,Software Engineers and Developers: Professionals in the software development industry who want to enhance their programming skills and gain a deeper understanding of how to choose and implement appropriate data structures for various applications.,Coding Enthusiasts: Individuals who have a passion for coding and want to strengthen their problem-solving skills.,Technical Interview Preparation: As data structures questions are common in technical interviews for software engineering positions, individuals preparing for such interviews will find this course beneficial.,Anyone Interested in Software Development: Individuals interested in learning more about software development, regardless of their academic or professional background, can benefit from a data structures course to improve their programming skills.