Curso gratuito

Computability, Complexity & Algorithms

by
Georgia Institute of Technology

The Power and Limitation of Algorithms

Programa Nanodegree

Engenheiro de Machine Learning

byKaggle

Evolua em sua carreira com um certificado que antecipa seu sucesso profissional.

Sobre este curso

This class is offered as CS6505 at Georgia Tech where it is a part of the Online Masters Degree (OMS). Taking this course here will not earn credit towards the OMS degree.

In this course, we will ask the big questions, “What is a computer? What are the limits of computation? Are there problems that no computer will ever solve? Are there problems that can’t be solved quickly? What kinds of problems can we solve efficiently and how do we go about developing these algorithms?” Understanding the power and limitations of algorithms helps us develop the tools to make real-world computers smarter, faster and safer.

Legendas
Inglês
Tempo estimadoTempo total entre hoje e dia da formatura depende do seu compromisso semanal. Em média, os nossos graduados completam este nanodegree em 3 semanas
Aprox. 3 semanas
Nível de conhecimento
avançado
Incluído no produto

Videoaulas

Testes interativos

Aulas com profissionais do setor

Ritmo individual de aprendizado

Comunidade de apoio aos alunos

Juntos rumo ao sucesso

Este curso é seu primeiro passo em direção a uma carreira com o programa Engenheiro de Machine Learning .

Curso gratuito

Computability, Complexity & Algorithms

porGeorgia Institute of Technology

Aumente seu conjunto de habilidades e suas chances de contratação com um modelo de aprendizagem inovador e independente.

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Pré-requisitos e exigências

Students are expected to have a solid grasp of the basics of discrete mathematics. Discrete Mathematics and Its Applications by Ken Rosen provides an excellent background for this course.

If you answer “no” to any of the following questions, it may be beneficial to acquire background knowledge concurrently or prior to taking the course.

  1. Can you show that the sum of the first n numbers is n(n+1)/2? Can you give the proof as an induction on n?
  2. Can you give an O(n log n) algorithm for sorting n numbers?
  3. Can you describe the difference between breadth-first and depth-first search?
  4. Given an nxn matrix A and an n-dimensional vector b, can you give a polynomial-time algorithm to find a vector x such that Ax=b?

Veja os requisitos tecnológicos necessários para fazer um curso na Udacity.

Responsáveis pelo curso

Charles Brubaker

Charles Brubaker

Instrutor

Lance Fortnow

Lance Fortnow

Instrutor

Hariharan Venkateswaran

Hariharan Venkateswaran

Instrutor

Por que fazer este curso?

You will learn a wealth of tools and techniques that will help you recognize when problems you encounter in the real-world are intractable and when there an efficient solution. This can save you countless hours that otherwise would have been spent on a fruitless endeavor or in re-inventing the wheel.

Quais são os benefícios?
Vídeos dos instrutoresExercícios práticosAulas com profissionais do setor