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The Data Structures course provides a comprehensive exploration of fundamental and advanced concepts essential for understanding and implementing efficient data organization and manipulation techniques. Through a series of carefully structured lectures, students delve into the core principles behind arrays, linked lists, stacks, queues, trees, and graphs. Beginning with introductory discussions on basic operations and traversals, the course progresses to more intricate topics such as binary search trees, heaps, hash tables, and advanced graph algorithms like shortest paths and minimum spanning trees. Emphasis is placed on both theoretical understanding and practical implementation, equipping learners with the necessary skills to design and analyze algorithms, optimize data storage, and solve complex problems efficiently. With a focus on real-world applications and problem-solving strategies, this course equips students with a solid foundation in Data Structures essential for success in software development and computer science domains.

Learn Data Structures with SDE working at Amazon

  • Upon completing the Data Structures course, students will:

    • Demonstrate a thorough understanding of fundamental data structures including arrays, linked lists, stacks, queues, trees, graphs, and their associated operations.
    • Apply appropriate data structures to solve a variety of computational problems efficiently, considering factors such as time complexity and space efficiency.
    • Design and implement algorithms for traversing, searching, sorting, and manipulating data within various data structures.
    • Analyze the performance characteristics of different data structures and algorithms, including their strengths, weaknesses, and suitability for specific problem domains.
    • Utilize advanced data structures such as binary search trees, heaps, hash tables, and trie data structures in the development of efficient and scalable software solutions.
    • Apply graph algorithms including breadth-first search (BFS), depth-first search (DFS), shortest paths, minimum spanning trees, and topological sorting to model and solve real-world problems.
    • Develop practical problem-solving skills through hands-on programming assignments, projects, and exercises that reinforce theoretical concepts and encourage critical thinking.
    • Communicate effectively about data structures, algorithms, and problem-solving strategies, both orally and in written form, to technical and non-technical audiences.
    • Cultivate a mindset of continuous learning and exploration in the field of data structures and algorithms, recognizing their central role in computer science and software engineering disciplines.
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