This course offers an in-depth exploration of Data Structures and their associated Algorithms, focusing on both theoretical constructs and real-world implementation in C++. Designed for aspiring software developers and computer scientists, the curriculum emphasizes the efficient storage, manipulation, and retrieval of data to solve computational problems.
- Delve into the concept of Abstract Data Types, which define operations independently of their implementation.
- Differentiate between ADTs and Data Structures, highlighting their interplay in software engineering.
- Master arrays as a linear, contiguous Data Structure.
- Implement multi-dimensional arrays and learn efficient memory management techniques in C++.
- Understand Last-In-First-Out (LIFO) and First-In-First-Out (FIFO) principles.
- Implement stacks and queues using static arrays, dynamic arrays, and circular arrays.
- Analyze their operational complexities and trade-offs in system-level programming.
- Cultivate a deep understanding of memory addressing and pointer arithmetic.
- Master the utilization of references and dereferencing for robust and flexible programming.
- Explore the application of pointers in dynamic memory management and interfacing with hardware.
- Explore runtime memory allocation using malloc, calloc, and new operators in C++.
- Address challenges such as fragmentation, memory leaks, and dangling pointers, and implement strategies for their mitigation.
- Understand the importance of RAII (Resource Acquisition Is Initialization) for efficient resource management.
- Implement Linked Lists, Linked Stacks, and Linked Queues using node-based architectures.
- Explore singly linked lists, doubly linked lists, and circular linked lists for flexible memory usage.
- Harness non-contiguous memory allocation to dynamically manage datasets of varying sizes.
- Evaluate algorithms using asymptotic notations such as Big O, Big Theta (Θ), and Big Omega (Ω).
- Conduct time complexity and space complexity analysis to optimize performance.
- Explore amortized analysis for understanding average-case behavior in dynamic systems.
- Implement fundamental algorithms such as:
- Linear Search and Binary Search for efficient data retrieval.
- Bubble Sort, Quick Sort, Merge Sort, and Heap Sort for data organization.
- Conduct best-case, worst-case, and average-case performance analysis for these algorithms.
- Design Hash Tables with open addressing and chaining for collision resolution.
- Explore Graphs, including directed, undirected, and weighted graphs, and their representations using adjacency matrices and adjacency lists.
- Master Trees and specialized variants such as Binary Trees, Binary Search Trees (BSTs), and Balanced Trees like AVL and Red-Black Trees.
- Learn advanced traversal algorithms like Depth-First Search (DFS) and Breadth-First Search (BFS).
By completing this course, you will:
- Gain proficiency in implementing and manipulating complex Data Structures in C++.
- Develop an analytical approach to evaluating algorithmic efficiency using rigorous mathematical techniques.
- Master memory management and mitigate risks such as fragmentation and resource mismanagement.
- Build a strong foundation for advanced topics such as graph theory, dynamic programming, and database indexing.
- To earn the CS201 Course Completion Certificate, you must score 70% or higher on the Final Exam.
- The certificate validates your proficiency in foundational Data Structures and Algorithms, a critical skillset for advanced computing roles.
This course is a rigorous journey into the realm of computational theory and practical engineering, equipping you with the technical acumen required for tackling real-world software development challenges.
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