Data Structures and Algorithms: The Complete Masterclass

Packt via Coursera Specialization

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Master the essential principles of data structures and algorithms through this comprehensive course. From Big O notation and recursion to complex structures like graphs and trees, you’ll gain the skills needed to design and implement efficient algorithms using Python. This course lays the foundation for solving real-world problems and excelling in technical interviews. You'll begin with a deep dive into complexity analysis and Big O notation before progressing to core data structures such as arrays, linked lists, stacks, queues, trees, heaps, tries, and graphs. Hands-on segments walk you through implementing these structures with Python while highlighting their real-world use cases and efficiencies. Next, you'll explore fundamental and advanced sorting and searching algorithms, recursion strategies, and tree/graph traversals. You’ll cap off your learning by solving real-world coding challenges designed to simulate technical interviews and solidify your understanding through practical application. This course is perfect for computer science students, aspiring developers, and professionals preparing for technical interviews. A basic familiarity with Python and programming logic is helpful but not mandatory.

Syllabus

Course 1: Foundations of Data Structures and Algorithm Analysis
Course 2: Advanced Data Structures and Algorithms
Course 3: Interview Questions and Real-World Applications

Courses

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9 hours 55 minutes
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Master the intricacies of data structures and algorithms with this comprehensive course, designed to deepen your understanding of recursion, searching, sorting, and traversal techniques. Gain hands-on experience as you explore foundational concepts, analyze algorithmic complexities, and implement efficient solutions to real-world problems. The journey begins with recursion, where you’ll delve into function control, call stacks, and tree recursion, supplemented by practical examples like factorial computation. Next, you’ll tackle searching algorithms, from linear to binary search, diving into their complexities and recursive implementations for enhanced problem-solving skills. Advance further by mastering both elementary and advanced sorting techniques, including bubble, selection, insertion, quick, and merge sort. Each module walks you through implementation, visualization, and performance analysis. Conclude with tree and graph traversal algorithms, covering depth-first, breadth-first searches, and their applications in hierarchical and networked data structures. This course is perfect for computer science enthusiasts, aspiring software developers, and anyone keen on algorithm optimization. A basic understanding of programming is recommended to maximize your learning.
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12 hours 9 minutes
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Unlock the power of algorithms and data structures with this comprehensive course. Begin your journey by mastering essential concepts such as Big O notation, space complexity, and recursion. Through clear explanations and practical examples, you'll learn to analyze algorithm efficiency and optimize solutions for real-world challenges. Dive into fundamental data structures, including arrays, linked lists, stacks, queues, and hash tables. Explore advanced topics like trees, heaps, and tries, with insights into binary trees, AVL trees, and graph structures. Each module builds on the last, blending theory with hands-on coding in Python to solidify your understanding. The course emphasizes a step-by-step approach, making complex concepts accessible. Learn not just the "how" but also the "why," with practical applications such as priority queues, hashing, and dynamic programming. Whether it's mastering sorting algorithms or implementing efficient search methods, you'll gain the skills to solve problems efficiently. Designed for aspiring developers, computer science students, and professionals, this course requires basic programming knowledge. It's perfect for anyone ready to enhance their problem-solving abilities and prepare for technical interviews. With beginner-to-intermediate difficulty, you'll be well-equipped to tackle coding challenges confidently.
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10 hours 33 minutes
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Master the essential data structures and algorithms that form the foundation of programming problem-solving. In this practical, project-driven course, you’ll work through real-world interview questions and coding challenges to strengthen your logic, sharpen your skills, and build the confidence to tackle technical assessments and professional projects. Your journey begins with core data structures like stacks, queues, and linked lists, exploring both their implementation and application. You’ll then move into classic interview-style problems such as Two Sum, Min Stack, Max Stack, and linked list reversal, learning the underlying coding patterns and strategies that make these solutions efficient and reusable. As the modules progress, you’ll dive into binary trees and binary search trees, practicing both construction and inversion, before advancing to string manipulation problems such as Detect Capital, reverse strings, and longest palindromic substring. Each step includes hands-on demonstrations and guided explanations to ensure you not only understand the algorithms but also know how to apply them under pressure. By the end of this 13-module course, you will have: - Implemented and practiced essential data structures from scratch. - Solved classic algorithmic problems with confidence and clarity. - Built expertise in binary trees, search trees, and string manipulation. - Developed a strong foundation for technical interviews and real-world coding challenges. This course is ideal for aspiring software developers, computer science students, and professionals preparing for interviews. A basic knowledge of programming in Python, Java, or C++ is recommended, and the intermediate-level design ensures a balance of foundational learning and advanced problem-solving practices that will help anyone looking to perform better in their next programming interview.