The Data Structures & Algorithms course begins with a review of some important Java techniques and nuances in programming. The course requires some prior knowledge of Java and object-oriented programming, but not in data structures or algorithms.
DurationThe Data Structures & Algorithms course begins with a review of some important Java techniques and nuances in programming. The course requires some prior knowledge of Java and object-oriented programming, but not in data structures or algorithms.
You’ll be introduced to time complexity and threads this concept throughout all data structures and algorithms presented in the course, and you will work with the principles of data storage in Arrays and LinkedList nodes. In addition, you will program the low-level data structures – Singly, Circular, and Doubly LinkedLists – and explore edge cases and efficiency.
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In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments.
Models, algorithms, recurrences, summations, growth rates. Probabilistic tools, upper and lower bounds; worst-case and average-case analysis, amortized analysis, dynamization. Comparison-based algorithms: search, selection, sorting, hashing. Information extraction algorithms (graphs, databases).
Algorithms and data structures are the essential frameworks for solving almost any computer engineering problem.
Survey of advanced algorithms and data structures such as heaps and heapsort, quicksort, red-black trees, B-trees, hash tables, graph algorithms, divide and conquer algorithms, dynamic programming, and greedy algorithms. Methods for proving correctness and asymptotic analysis.
This course covers and relates fundamental components of programs. Students use various data structures to solve computational problems, and implement data structures using a high-level programming language.
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