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
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