Algorithms, Part I, is the first in a series of two sections on training and familiarity with algorithms and data structures provided by Princeton University . This collection covers essential information about algorithms and data structures that every programmer should know.
Elite The focus of this collection is more on the application of these algorithms and the scientific analysis of their implementation performance in Java. The first part of this course covers the basic data structures and sorting and search algorithms. During this course, you will first become familiar with the data structure of separate sets (Union-Find) and its various implementations, such as finding and combining fast and weighted and applying this type of data on the problem of seepage from physical chemistry.
Then, you will learn to analyze algorithms in a completely scientific way by measuring runtime, developing assumptions about performance, building a mathematical model to explain the behavior of the algorithm, and finally measuring the memory used by the Java program.
In the following sections, stack and queue structures and their implementation with linked lists and arrays and familiarity with two advanced Java features namely generics and iterators, degree and shell sorting algorithms, integration and its various versions, selective and Quicksort coverage Have been given.
Prioritize queues and implement with binary heap and sort with heapsort, dictionaries and implement with sorted array (binary search) and unordered list (sequential search) with its applications, balanced search trees and applications Its geometry and hash tables are other topics of this course.
What skills do you acquire:
- Data structure
- Programming with Java
Specifications of Algorithms, Part I:
- Publisher: Coursera
- Instructor: Kevin Wayne , Robert Sedgewick
- English language
- Level of education: Intermediate
- Number: 13 lessons in 6 sections
- Course duration: Approximately 53 hours
- Course Introduction – 10m
- Union − Find – 9h
- Analysis of Algorithms – 1h
- Stacks and Queues – 9h
- Elementary Sorts – 1h
- Mergesort – 9h
- Quicksort – 1h
- Priority Queues – 9h
- Elementary Symbol Tables – 2h
- Balanced Search Trees – 2h
- Geometric Applications of BSTs – 9h
- Hash Tables – 1h
- Symbol Table Applications – 26m
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