This course presents some fundamental data structures, including lists, stacks, queues, hashes, and binary trees. Students will master a number of algorithms including Mergesort and Quicksort.
DurationThis course presents some fundamental data structures, including lists, stacks, queues, hashes, and binary trees. Students will master a number of algorithms including Mergesort and Quicksort.
We will study techniques for analyzing the running time and space requirements of these algorithms, and of other algorithms based on the data structures. The goals for the course are for the students to analyze running times of algorithms, and to design algorithms using appropriate data structures to solve non-trivial computing problems.
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The analysis and design of computer algorithms and their underlying data structures. Analysis of the timing and efficiency of algorithms. Study of lists, stacks, queues, trees, backtracking, searching, sorting and recursion.
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.
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.
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.
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