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12/9/2020
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Algorithms Specialization is the name of a training set for thinking similar to a computer scientist, and with the help of this course, you will gain skills in the basic principles of designing and analyzing algorithms. Algorithms are the heart of computer science, and it has countless practical applications. This course set provides an introduction to algorithms for learners with little experience in programming. Although this course is relatively difficult, it emphasizes the general and conceptual overview of your understanding of low and partial math implementation. At the end of this course you will reach a level where you excel in technical interviews and talk algorithms psychologically with other programmers and computer scientists.
Algorithms
Dynamic programming
Greedy algorithm
Segmentation and conquest algorithms
Randomization algorithm
Sorting algorithm
Charts
Data structure
Hash Table
Below a graph of a graph
Np-Completeness
Publisher: Coursera Instructor: Tim Roughgarden English language Level of education: Intermediate Number of courses: 4 Duration: 37 hours and 1 minute
COURSE 1 Divide and Conquer, Sorting and Searching, and Randomized Algorithms
COURSE 2 Graph Search, Shortest Paths, and Data Structures
COURSE 3 Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
COURSE 4 Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
Learners should know how to program in at least one programming language (like C, Java, or Python); some familiarity with proofs, including proofs by induction and by contradiction; and some discrete probability, like how to compute the probability that a poker hand is a full house. At Stanford, a version of this course is taken by sophomore, junior, and senior-level computer science majors.
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Subtitle: English and other languages
Quality: 720
This collection includes 4 different courses.
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