The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second). Do you have technical problems? Write to us: coursera@hse.ru
Overview
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Destrezas que aprenderás
Dynamic Programming, Debugging, Software Testing, Algorithms, Computer Programming
Revisiones
PR
Feb 10, 2019
The course is perfectly designed. The perfect start for those who start with data structures and algorithms. The Dynamic programming was a little bit tough but overall course is perfectly designed
AG
Feb 19, 2018
best course for clearing basics of algorithms as well as learning by doing and blow your mind by thinking hard from different prospectives to get desired solutions of programming assignments ...
De la lección
Divide-and-Conquer
In this module you will learn about a powerful algorithmic technique called Divide and Conquer. Based on this technique, you will see how to search huge databases millions of times faster than using naïve linear search. You will even learn that the standard way to multiply numbers (that you learned in the grade school) is far from the being the fastest! We will then apply the divide-and-conquer technique to design two efficient algorithms (merge sort and quick sort) for sorting huge lists, a problem that finds many applications in practice. Finally, we will show that these two algorithms are optimal, that is, no algorithm can sort faster!
Impartido por:
Alexander S. Kulikov
Visiting Professor
Michael Levin
Lecturer
Neil Rhodes
Adjunct Faculty
Pavel Pevzner
Professor
Daniel M Kane
Assistant Professor
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