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    Mastering Algorithms: Practical Approach To Solving Problems

    Posted By: ELK1nG
    Mastering Algorithms: Practical Approach To Solving Problems

    Mastering Algorithms: Practical Approach To Solving Problems
    Published 2/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 975.34 MB | Duration: 4h 18m

    Algorithmic Symphony: Harmonizing Sorting, Dynamic Programming, Recursion, and Backtracking

    What you'll learn

    Understanding Fundamental Concepts: Develop a strong foundation in algorithmic principles

    Problem-Solving Skills: Cultivate the ability to analyze complex problems and devise efficient algorithms to solve them.

    Algorithm Design Techniques: Explore various algorithm design techniques, including brute force, recursion, and optimization strategies.

    Data Structures Integration: Integrate algorithms with essential data structures such as arrays, linked lists, trees, and graphs

    Practical Applications and Optimization: Apply algorithms to real-world scenarios and understand how to optimize code for better performance

    Requirements

    A solid understanding of at least one programming language is crucial

    Description

    Unlock the secrets of efficient problem-solving and algorithmic optimization with our "Mastering Algorithms" course. Whether you're a computer science student, a seasoned software engineer, or an aspiring coder, this course is designed to elevate your understanding of algorithm design, implementation, and analysis.Course Highlights:1. Foundational Concepts: Dive deep into the fundamental concepts of algorithmic design, data structures, and their practical applications. Understand time and space complexity, and develop a solid foundation in algorithmic thinking.2. Sorting and Searching Mastery: Explore a spectrum of sorting algorithms and searching techniques. From basic to advanced, learn how to choose the right approach for different scenarios and optimize your code for efficiency.3. Dynamic Programming Unveiled: Demystify the power of dynamic programming. Discover how to break down complex problems into simpler subproblems and optimize solutions for improved efficiency. Real-world applications and case studies will reinforce your understanding.4. Recursive Wisdom: Delve into the elegance of recursive algorithms. Master the art of problem decomposition, understand the divide-and-conquer approach, and apply recursion to solve a variety of problems efficiently.5. Backtracking Techniques: Learn systematic exploration with backtracking. Navigate complex problem spaces, make informed decisions, and discover how backtracking can be a powerful tool for solving problems with multiple solutions.6. Real-world Applications: Bridge the gap between theory and practice by applying algorithms to real-world scenarios. Work on hands-on projects and case studies that simulate industry challenges, preparing you for practical algorithmic problem-solving.7. Optimizing Code: Gain insights into optimizing code for better performance. Understand the importance of algorithmic efficiency in software development and learn best practices for writing scalable and maintainable code.8. Interactive Learning: Engage in a dynamic learning environment with interactive quizzes, coding exercises, and collaborative projects. Benefit from personalized feedback to enhance your problem-solving skills.By the end of this course, you will not only have a comprehensive understanding of various algorithms but also the ability to approach complex problems with confidence and devise efficient solutions. Join us on a journey to master the art and science of algorithms and elevate your coding skills to new heights.

    Overview

    Section 1: Recursion

    Lecture 1 Introduction

    Lecture 2 Pros & Cons

    Lecture 3 Example

    Lecture 4 Math Induction

    Lecture 5 Math Function

    Lecture 6 Iterative

    Lecture 7 Coding: Factorial

    Lecture 8 Coding: Fibonacci

    Lecture 9 Tail Recursion

    Lecture 10 Indirect Recusion

    Section 2: Sorting

    Lecture 11 Introduction

    Lecture 12 Comparison based Sorting Algorithms

    Lecture 13 Bubble Sort

    Lecture 14 Coding: Bubble Sort

    Lecture 15 Selection Sort

    Lecture 16 Visual: Selection Sort

    Lecture 17 Coding: Selection Sort

    Lecture 18 Visual: Insertion Sort

    Lecture 19 Coding: Insertion Sort

    Section 3: Divide & Conquer

    Lecture 20 Introduction

    Lecture 21 Recursion

    Lecture 22 Divide Phase

    Lecture 23 Conquer Phase

    Lecture 24 Merge Sort

    Lecture 25 Visual: Merge Sort

    Lecture 26 Coding: Merge Sort

    Lecture 27 Quick Sort

    Lecture 28 Coding: Quick Sort

    Section 4: Backtracking

    Lecture 29 Introduction

    Lecture 30 Coding: N-Queens

    Section 5: Dynamic Programming

    Lecture 31 Introduction

    Lecture 32 Memoization

    Lecture 33 Coding: Memoization

    Lecture 34 Tabulation

    Lecture 35 Coding: Tabulation

    Lecture 36 Patterns

    Lecture 37 States and Transitions

    Lecture 38 Problem: Maximum Deliciousness

    Lecture 39 Coding: Maximum Deliciousness

    Lecture 40 Complexity: Maximum Deliciousness

    Lecture 41 Coding: Maximum Deliciousness (Top Down)

    Lecture 0 Coding: Maximum Deliciousness (Bottom Up)

    Section 6: Sliding Window

    Lecture 42 Introduction

    Lecture 43 Fixed Size Sliding Window

    Lecture 44 Coding: Maximum Sum of Subarray

    Lecture 45 Variable Size Sliding Window

    Lecture 0 Visual: Minimum Length of Subarray

    Lecture 0 Coding: Variable Size Sliding Window

    Lecture 0 Introduction

    Lecture 0 Coding: Two Pointers

    Computer Science Students,Software Engineers and Developers,Coding Enthusiasts,Anyone Interested in Problem Solving