4.7
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1,230 classificações

Susan Davidson

91.629 já se inscreveram

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Parte da graduação Master of Computer and Information Technology
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Computational Thinking for Problem Solving

Universidade da Pensilvânia

Informações sobre o curso

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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.   
In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language.  By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program. 

This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.

Prazos flexíveis

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Certificados compartilháveis

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100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Nível iniciante

Aprox. 18 horas para completar

Inglês

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Habilidades 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

Sua empresa se beneficiaria do treinamento dos funcionários em habilidades sob demanda?

Experimente o Coursera for Business

Instrutores

Classificação do instrutor

4,84/5 (374 classificações)

Susan Davidson

Weiss Professor

Computer & Information Science

91.921 aprendizes

4 Cursos

oferecido por

Universidade da Pensilvânia

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Este curso é parte da graduação 100% on-line Master of Computer and Information Technology da Universidade da Pensilvânia. Caso seja aceito para o programa completo, seus cursos contarão para sua graduação.

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Programa - O que você aprenderá com este curso

Classificação do conteúdo87%(5,444 classificações)

Semana

Semana 1

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.)

Semana

Semana 2

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.)

Semana

Semana 3

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.)

6 videos

3.1 A History of the Computer7min

3.2 Intro to the von Neumann Architecture8min

3.3 von Neumann Architecture Data6min

3.4 von Neumann Architecture Control Flow5min

3.5 Expressing Algorithms in Pseudocode8min

3.6 Case Studies10min

5 exercícios práticos

3.1 A History of the Computer10min

3.2 Intro to the von Neumann Architecture10min

3.3 von Neumann Architecture Data10min

3.4 von Neumann Architecture Control Flow10min

3.5 Expressing Algorithms in Pseudocode10min

Semana

Semana 4

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

9 videos

4.1 Introduction to Python6min

4.2 Variables13min

4.3 Conditional Statements8min

4.4 Lists7min

4.5 Iteration14min

4.6 Functions10min

4.7 Classes and Objects9min

4.8 Case Studies11min

4.9 Course Conclusion8min

12 leituras

Programming on the Coursera Platform10min

Python Playground

Variables Programming Activity20min

Solution to Variables Programming Activity10min

Conditionals Programming Activity20min

Solution to Conditionals Programming Activity10min

Solution to Lists Programming Assignment5min

Solution to Loops Programming Assignment10min

Solution to Functions Programming Assignment10min

Solution to Challenge Programming Assignment10min

Solution to Classes and Objects Programming Assignment10min

Solution to Project Part 410min

12 exercícios práticos

4.2 Variables10min

4.3 Conditional Statements5min

4.4 Lists10min

Lists Programming Assignment15min

4.5 Iteration10min

Loops Programming Assignment30min

4.6 Functions10min

Functions Programming Assignment20min

(Optional) Challenge Programming Assignment20min

4.7 Classes and Objects10min

Classes and Objects Programming Assignment20min

Project Part 4: Implementing the Solution in Python25min

Avaliações

4.7

422 avaliações

5 stars
80,56%
4 stars
12,68%
3 stars
3,25%
2 stars
1,21%
1 star
2,27%

Principais avaliações do COMPUTATIONAL THINKING FOR PROBLEM SOLVING

por NA14 de jan de 2021

IT is a very good course. That being said, week 4 should be spread over two weeks, and have more explanation in order to make the projects more manageable. I struggled with the last two projects.

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 JL8 de fev de 2020

Great course - the non-programming parts (making flow charts etc) were actually more difficult than the programming (simple Python programming - my first time programming in python)

por EN18 de ago de 2019

The autograder can be somewhat of a pain and some of the solutions in the peer-review sections aren't the most efficient. Otherwise it helped teach the building blocks of coding.

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Perguntas Frequentes – FAQ

Quando terei acesso às palestras e às tarefas?
O acesso a palestras e tarefas depende do tipo de inscrição. Se você participar de um curso como ouvinte, você poderá ver quase todo o conteúdo do curso gratuitamente. Para acessar tarefas valendo nota e obter um Certificado, você precisará adquirir a experiência do Certificado, durante ou após a participação como ouvinte. Se você não vir a opção de participar como ouvinte:
o curso pode não oferecer essa opção. Você pode experimentar um teste gratuito ou solicitar o auxílio financeiro.
Em vez disso, o curso pode oferecer 'Curso completo, sem Certificado'. Com esta opção, é possível ver todo o conteúdo do curso, enviar as avaliações necessárias e obter uma nota final. Isso também significa que você não poderá comprar uma experiência de Certificado.
O que recebo ao adquirir o Certificado?
Quando você adquire o Certificado, ganha acesso a todo o material do curso, incluindo avaliações com nota atribuída. Após concluir o curso, seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
Existe algum auxílio financeiro disponível?
Sim. Em programas de aprendizado selecionados, você pode solicitar auxílio financeiro ou uma bolsa de estudos caso não consiga pagar a taxa de inscrição. Se o auxílio financeiro ou bolsa de estudos estiver disponível para a seleção do seu programa de aprendizado, você encontrará um link para se inscrever na página de descrição.
Do I need to know how to program or have studied computer science in order to take this course?
No, definitely not! This course is intended for anyone who has an interest in approaching problems more systematically, developing more efficient solutions, and understanding how computers can be used in the problem solving process. No prior computer science or programming experience is required.
How much math do I need to know to take this course?
Some parts of the course assume familiarity with basic algebra, trigonometry, mathematical functions, exponents, and logarithms. If you don’t remember those concepts or never learned them, don’t worry! As long as you’re comfortable with multiplication, you should still be able to follow along. For everything else, we’ll provide links to references that you can use as a refresher or as supplemental material.
Does this course prepare me for the Master of Computer and Information Technology (MCIT) degree program at the University of Pennsylvania?
This course will help you discover whether you have an aptitude for computational thinking and give you some beginner-level experience with online learning. In this course you will learn several introductory concepts from MCIT instructors produced by the same team that brought the MCIT degree online.
If you have a bachelor's degree and are interested in learning more about computational thinking, we encourage you to apply to MCIT On-campus (http://www.cis.upenn.edu/prospective-students/graduate/mcit.php) or MCIT Online (https://onlinelearning.seas.upenn.edu/mcit/). Please mention that you have completed this course in the application.
Where can I find more information about the Master of Computer and Information Technology (MCIT) degree program at the University of Pennsylvania?
Use these links to learn more about MCIT:
MCIT On-campus: http://www.cis.upenn.edu/prospective-students/graduate/mcit.php
MCIT Online: https://onlinelearning.seas.upenn.edu/mcit/

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Computational Thinking for Problem Solving

Computational Thinking for Problem Solving

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