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.
Este curso forma parte de Programa especializado: Data Science Foundations: Data Structures and Algorithms
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Programa especializado: Data Science Foundations: Data Structures and AlgorithmsUniversidad de Colorado en BoulderAcerca de este Curso
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100Â % en lÃnea
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Nivel intermedio
Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. Some programming experience with Python.
Aprox. 35 horas para completar
Inglés (English)
SubtÃtulos: Inglés (English)
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Prueba Coursera para negociosQué aprenderás
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
Habilidades que obtendrás
- Analysis of Algorithms
- Hashtables
- Algorithm Design
- Python Programming
- Data Structure Design
Fechas lÃmite flexibles
Restablece las fechas lÃmite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100Â % en lÃnea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Calculus: derivatives and integrals. Probability theory: distributions, expectations, and moments. Some programming experience with Python.
Aprox. 35 horas para completar
Inglés (English)
SubtÃtulos: Inglés (English)
¿PodrÃa tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?
Prueba Coursera para negocios
ofrecido por
Universidad de Colorado en 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.
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Este curso forma parte de un programa de grado ofrecido por Universidad de Colorado en Boulder. Si te inscribes en un curso sin tÃtulo de grado a través de la universidad y lo completas en lÃnea, cuenta como horas de crédito para un programa de grado en CU-Boulder. Todo lo que tienes que hacer es solicitarlo a través de la universidad.
Programa - Qué aprenderás en este curso
10 horas para completar
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 horas para completar
7 videos (Total 202 minutos), 10 lecturas, 5 cuestionarios
9 horas para completar
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 horas para completar
5 videos (Total 120 minutos), 6 lecturas, 6 cuestionarios
9 horas para completar
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 horas para completar
7 videos (Total 152 minutos), 6 lecturas, 6 cuestionarios
6 horas para completar
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 horas para completar
5 videos (Total 113 minutos), 6 lecturas, 2 cuestionarios
Reseñas
- 5 stars83,33Â %
- 4 stars10,93Â %
- 3 stars2,08Â %
- 2 stars1,04Â %
- 1 star2,60Â %
Principales reseñas sobre ALGORITHMS FOR SEARCHING, SORTING, AND INDEXING
por WW15 de oct. de 2021
Instructor was great. Exercises in Jupyter were awesome.
Only negative is many videos referenced another course, but that isn't a big deal.
por UK16 de jun. de 2022
It is amazing course which I have taken and learn algorithm .
por DM22 de jul. de 2021
Love Prof Sriram's teaching style, very clear and approachable.
por T24 de jul. de 2022
Very engaging and clear lessons and quizzes. There're only some typos but they don't hinder the learning process
Acerca de Programa especializado: 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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