This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Data Science Foundations: Data Structures and Algorithms
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Spezialisierung Data Science Foundations: Data Structures and AlgorithmsUniversity of Colorado BoulderÜber diesen Kurs
49.959 kürzliche Aufrufe
Flexible Fristen
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Zertifikat zur Vorlage
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100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Mittel“
Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. Some programming experience with Python.
Ca. 34 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Was Sie lernen werden
Explain fundamental concepts for algorithmic searching and sorting
Describe heap data structures and analyze heap components, such as arrays and priority queues
Design basic algorithms to implement sorting, selection, and hash functions in heap data structures
Kompetenzen, die Sie erwerben
- Analysis of Algorithms
- Hashtables
- Algorithm Design
- Python Programming
- Data Structure Design
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Stufe „Mittel“
Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. Some programming experience with Python.
Ca. 34 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.
Dieses Kurs ist Teil des reinen Onlineabschlusses Master of Science in Data Science von University of Colorado Boulder.
Wenn Sie in das komplette Programm aufgenommen werden, werden Ihre Kurse auf Ihren Abschluss angerechnet.
Lehrplan - Was Sie in diesem Kurs lernen werden
10 Stunden zum Abschließen
Basics of Algorithms Through Searching and Sorting
In this module the student will learn the very basics of algorithms through three examples: insertion sort (sort an array in ascending/descending order); binary search: search whether an element is present in a sorted array and if yes, find its index; and merge sort (a faster method for sorting an array). Through these algorithms the student will be introduced to the analysis of algorithms -- i.e, proving that the algorithm is correct for the task it has been designed for and establishing a bound on how the time taken to execute the algorithm grows as a function of input. The student is also exposed to the notion of a faster algorithm and asymptotic complexity through the O, big-Omega and big-Theta notations.
10 Stunden zum Abschließen
7 Videos (Gesamt 202 min), 9 Lektüren, 5 Quiz
9 Stunden zum Abschließen
Heaps and Hashtable Data Structures
In this module, the student will learn about the basics of data structures that organize data to make certain types of operations faster. The module starts with a broad introduction to data structures and talks about some simple data structures such as first-in first out queues and last-in first out stack. Next, we introduce the heap data structure and the basic properties of heaps. This is followed by algorithms for insertion, deletion and finding the minimum element of a heap along with their time complexities. Finally, we will study the priority queue data structure and showcase some applications.
9 Stunden zum Abschließen
5 Videos (Gesamt 120 min), 6 Lektüren, 6 Quiz
9 Stunden zum Abschließen
Randomization: Quicksort, Quickselect, and Hashtables
We will go through the quicksort and quickselect algorithms for sorting and selecting the kth smallest element in an array efficiently. This will also be an introduction to the role of randomization in algorithm design. Next, we will study hashtables: a highly useful data structure that allows for efficient search and retrieval from large amounts of data. We will learn about the basic principles of hash-table and operations on hashtables.
9 Stunden zum Abschließen
7 Videos (Gesamt 152 min), 6 Lektüren, 6 Quiz
6 Stunden zum Abschließen
Applications of Hashtables
In this module, we will learn randomized pivot selection for quicksort and quickselect. We will learn how to analyze the complexity of the randomized quicksort/quickselect algorithms. We will learn open address hashing: a technique that simplifies hashtable design. Next we will study the design of hash functions and their analysis. Finally, we present and analyze Bloom filters that are used in various applications such as querying streaming data and counting.
6 Stunden zum Abschließen
5 Videos (Gesamt 113 min), 6 Lektüren, 2 Quiz
Bewertungen
Top-Bewertungen von ALGORITHMS FOR SEARCHING, SORTING, AND INDEXING
von ST10. Aug. 2021
this is the best course on data structures that i have found! Pr. Sriram Sankaranarayanan thank you! if i was a multi-billionaire i would definitely donate a check to you for this wonderful course :)
von SK2. Okt. 2021
Well laid out course which is both concise and has elaborate assignments which help in learning the concepts well. Many thanks to the professor for his effort.
von WW15. Okt. 2021
Instructor was great. Exercises in Jupyter were awesome. Only negative is many videos referenced another course, but that isn't a big deal.
von ZK21. Juni 2021
Great course. Concise towards the applications and not too theory heavy.
Über den Spezialisierung Data Science Foundations: Data Structures and Algorithms
Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing. This course will teach the fundamentals of data structures and algorithms with a focus on data science applications. This specialization is targeted towards learners who are broadly interested in programming applications that process large amounts of data (expertise in data science is not required), and are familiar with the basics of programming in python. We will learn about various data structures including arrays, hash-tables, heaps, trees and graphs along with algorithms including sorting, searching, traversal and shortest path algorithms.
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