Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
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Computational Thinking for Problem Solving
Universidade da PensilvâniaInformações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível iniciante
Aprox. 18 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Sua empresa se beneficiaria do treinamento dos funcionários em habilidades sob demanda?
Experimente o Coursera for BusinessHabilidades que você terá
- Simple Algorithm
- Python Programming
- Problem Solving
- Computation
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível iniciante
Aprox. 18 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Sua empresa se beneficiaria do treinamento dos funcionários em habilidades sob demanda?
Experimente o Coursera for Business
oferecido por
Universidade da Pensilvânia
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
Comece a trabalhar rumo ao seu mestrado
Este curso está relacionado à graduação Master of Computer and Information Technology 100% on-line pela Universidade da Pensilvânia. Ele fornecerá uma prévia dos tópicos, materiais e instrutores para que você possa decidir se o programa de graduação on-line completo é adequado para você.
Programa - O que você aprenderá com este curso
3 horas para concluir
Pillars of Computational Thinking
Computational thinking is an approach to solving problems using concepts and ideas from computer science, and expressing solutions to those problems so that they can be run on a computer. As computing becomes more and more prevalent in all aspects of modern society -- not just in software development and engineering, but in business, the humanities, and even everyday life -- understanding how to use computational thinking to solve real-world problems is a key skill in the 21st century.
3 horas para concluir
6 vídeos (Total 44 mín.)
4 horas para concluir
Expressing and Analyzing Algorithms
When we use computational thinking to solve a problem, what we’re really doing is developing an algorithm: a step-by-step series of instructions. Whether it’s a small task like scheduling meetings, or a large task like mapping the planet, the ability to develop and describe algorithms is crucial to the problem-solving process based on computational thinking. This module will introduce you to some common algorithms, as well as some general approaches to developing algorithms yourself. These approaches will be useful when you're looking not just for any answer to a problem, but the best answer. After completing this module, you will be able to evaluate an algorithm and analyze how its performance is affected by the size of the input so that you can choose the best algorithm for the problem you’re trying to solve.
4 horas para concluir
7 vídeos (Total 69 mín.)
4 horas para concluir
Fundamental Operations of a Modern Computer
Computational thinking is a problem-solving process in which the last step is expressing the solution so that it can be executed on a computer. However, before we are able to write a program to implement an algorithm, we must understand what the computer is capable of doing -- in particular, how it executes instructions and how it uses data. This module describes the inner workings of a modern computer and its fundamental operations. Then it introduces you to a way of expressing algorithms known as pseudocode, which will help you implement your solution using a programming language.
4 horas para concluir
6 vídeos (Total 46 mín.)
7 horas para concluir
Applied Computational Thinking Using Python
Writing a program is the last step of the computational thinking process. It’s the act of expressing an algorithm using a syntax that the computer can understand. This module introduces you to the Python programming language and its core features. Even if you have never written a program before -- or never even considered it -- after completing this module, you will be able to write simple Python programs that allow you to express your algorithms to a computer as part of a problem-solving process based on computational thinking.
7 horas para concluir
9 vídeos (Total 91 mín.), 12 leituras, 12 testes
Avaliações
- 5 stars80,38%
- 4 stars12,82%
- 3 stars3,26%
- 2 stars1,25%
- 1 star2,26%
Principais avaliações do COMPUTATIONAL THINKING FOR PROBLEM SOLVING
por DA5 de fev de 2021
A good introduction to computer science that sees some theoretical concepts discussed and demonstrated, before introducing you to simple algorithm design and problem-solving using Python.
por MS4 de mai de 2020
A really well-taught course by astute professors. Its assignments are to the point and not much abstract with good amount of challenging questions especially the last module of the course
por AW3 de fev de 2019
The course is very well-designed and it helped me develop understand how to apply computational thinking in solving various types of problems as well as acquire basic skills of programming in Python.
por QT3 de mar de 2019
The course is generally good. However, the assignment content and the lecture are not really getting along, especially the Python part. I suggest more "bridging" materials.
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