Algorithms and Data Structures (Computer Science Fundamentals)

✍ Scribed by Edet, Theophilus

• Publisher: CompreQuest Books
• Year: 2023
• Tongue: English
• Leaves: 265
• Series: Computer Science Fundamentals
• Category: Library

✦ Synopsis

Unlock the Power of Algorithmic Wizardry and Data Structures Galore!
In the ever-evolving landscape of technology, algorithms and data structures are the unsung heroes behind every remarkable software, application, or system you encounter. They are the magic wand that transforms complex problems into elegant solutions. Are you ready to wield that wand?
"Algorithms and Data Structures" is your comprehensive guide to mastering the core principles that drive the digital world. Whether you're a seasoned programmer looking to sharpen your skills or a newcomer to the world of computer science, this book is your passport to a realm where innovation and efficiency reign supreme.
What Awaits You
Foundational Knowledge: Begin your journey with a solid grasp of fundamental concepts, terminology, and problem-solving techniques.
Algorithmic Wizardry: Explore a world of algorithms, from sorting and searching to dynamic programming, greedy techniques, and more. Uncover the secrets of crafting efficient, elegant, and error-free code.
Data Structures Galore: Dive deep into a treasure trove of data structures, from arrays and linked lists to trees, graphs, and specialized structures. Learn their inner workings and discover when and where to use each one.
Real-World Applications: See how algorithms and data structures are applied in practical scenarios, from web development and mobile apps to artificial intelligence and data science.
Hands-On Practice: Cement your understanding with hands-on coding exercises and projects that bridge the gap between theory and practice.
Why This Book Matters
Unlock Career Opportunities: Gain the skills that top tech companies value in their engineers and developers. Ace technical interviews and climb the career ladder with confidence.
Enhance Problem-Solving: Sharpen your problem-solving skills and develop a mindset that enables you to tackle complex challenges with ease.
Create Innovative Solutions: Harness the power of algorithms and data structures to build efficient, innovative, and scalable software solutions.
Empower Your Future: The knowledge you gain from this book will empower you to shape the future of technology and make a meaningful impact on the digital world.
Don't just use technology—understand it. With "Algorithms and Data Structures" as your guide, you'll unlock the door to a world of endless possibilities. Whether you're a student, a professional, or simply a curious mind, this book will empower you to turn ideas into reality and problems into solutions. Get ready to embark on a transformative journey into the heart of computer science. Your adventure begins now!

✦ Table of Contents

Preface
Algorithms and Data Structures
Module 1: Introduction to Algorithms and Data Structures
Module 1: Introduction to Algorithms and Data Structures
Introduction to Algorithms
Importance of Data Structures
Algorithm Analysis and Big O Notation
Basic Python Programming Review
Module 2: Fundamentals of Data Structures
Module 2: Fundamentals of Data Structures
Arrays and Linked Lists
Stacks and Queues
Hash Tables
Trees and Graphs
Module 3: Sorting Algorithms
Module 3: Sorting Algorithms
Selection Sort
Insertion Sort
Merge Sort
Quick Sort
Module 4: Searching Algorithms
Module 4: Searching Algorithms
Linear Search
Binary Search
Hashing for Searching
Depth-First Search and Breadth-First Search
Module 5: Advanced Data Structures
Module 5: Advanced Data Structures
Priority Queues and Heaps
AVL Trees and Red-Black Trees
B-Trees and B+ Trees
Disjoint-Set (Union-Find) Data Structure
Module 6: Dynamic Programming
Module 6: Dynamic Programming
Introduction to Dynamic Programming
Fibonacci Sequence using Dynamic Programming
Longest Common Subsequence
Knapsack Problem
Module 7: Graph Algorithms
Module 7: Graph Algorithms
Graph Representation
Dijkstra's Algorithm
Minimum Spanning Trees (Prim's and Kruskal's)
Topological Sorting
Module 8: Greedy Algorithms
Module 8: Greedy Algorithms
Introduction to Greedy Algorithms
Huffman Coding
Minimum Spanning Trees with Prim's Algorithm (Review)
Interval Scheduling
Module 9: Advanced Sorting Techniques
Module 9: Advanced Sorting Techniques
Radix Sort
External Sorting
Sorting in the Real World (e.g., Timsort)
Performance Analysis of Sorting Algorithms
Module 10: String Algorithms
Module 10: String Algorithms
String Matching (Naive and KMP)
Trie Data Structure
Edit Distance (Levenshtein Distance)
Regular Expressions
Module 11: Divide and Conquer Algorithms
Module 11: Divide and Conquer Algorithms
Introduction to Divide and Conquer
Matrix Multiplication
Closest Pair of Points
Strassen's Matrix Multiplication
Module 12: Geometric Algorithms
Module 12: Geometric Algorithms
Convex Hull (Graham's Scan)
Line Segment Intersection
Voronoi Diagrams
Computational Geometry Applications
Module 13: Advanced Data Structures - Part 2
Module 13: Advanced Data Structures - Part 2
Trie Data Structure (Review)
Suffix Trees and Suffix Arrays
Bloom Filters
Fenwick Trees (Binary Indexed Trees)
Module 14: Dynamic Programming - Part 2
Module 14: Dynamic Programming - Part 2
Longest Increasing Subsequence
Matrix Chain Multiplication
Dynamic Programming in Practice
Memoization vs. Tabulation
Module 15: Network Flow Algorithms
Module 15: Network Flow Algorithms
Ford-Fulkerson Algorithm
Max Flow-Min Cut Theorem
Applications of Network Flow
Bipartite Matching
Module 16: NP-Hard Problems and Approximation Algorithms
Module 16: NP-Hard Problems and Approximation Algorithms
Introduction to NP-Hardness
Traveling Salesman Problem
Approximation Algorithms
Greedy Approximations
Module 17: Randomized Algorithms
Module 17: Randomized Algorithms
Monte Carlo and Las Vegas Algorithms
Randomized Quick Sort
Primality Testing (Miller-Rabin)
Applications of Randomized Algorithms
Module 18: Parallel and Distributed Algorithms
Module 18: Parallel and Distributed Algorithms
Parallel Computing Models
Parallel Sorting Algorithms
Distributed Hash Tables
MapReduce and Parallel Processing
Module 19: Advanced Graph Algorithms
Module 19: Advanced Graph Algorithms
Strongly Connected Components (Kosaraju's Algorithm)
Maximum Flow Algorithms (Edmonds-Karp)
Bipartite Graphs and Matching (Review)
Graph Algorithms in Real-world Networks
Module 20: Advanced Topics in Data Structures
Module 20: Advanced Topics in Data Structures
Suffix Trees and Applications
Interval Trees and Segment Trees
Skip Lists
Treaps and Splay Trees
Module 21: Advanced Dynamic Programming
Module 21: Advanced Dynamic Programming
Longest Common Substring
Bitmask Dynamic Programming
Advanced DP Techniques
Dynamic Programming Optimization
Module 22: Online Algorithms
Module 22: Online Algorithms
Competitive Analysis
Paging Algorithms
Online Scheduling
Buffer Management
Module 23:Specialized Data Structures and Algorithms
Module 23:Specialized Data Structures and Algorithms
B-Trees and Databases
Geohash and Spatial Indexing
Compressed Data Structures
Quantum Algorithms (Introduction)
Module 24: Review and Project
Module 24: Review and Project
Comprehensive Review of Key Concepts
Final Project Presentation and Evaluation
Career and Further Learning
Course Conclusion and Future Directions