4.7
estrellas
1,230 calificaciones

87 %

Susan Davidson

91.742 ya inscrito

Ofrecido Por

Parte del título de grado Master of Computer and Information Technology
Más información

Computational Thinking for Problem Solving

Universidad de Pensilvania

Acerca de este Curso

99.248 vistas recientes

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.

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Nivel principiante

Aprox. 18 horas para completar

Inglés (English)

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Habilidades que obtendrás

Simple Algorithm
Python Programming
Problem Solving
Computation

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Nivel principiante

Aprox. 18 horas para completar

Inglés (English)

¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?

Prueba Coursera para negocios

Instructor

Calificación del instructor

4,84/5 (374 calificaciones)

Susan Davidson

Weiss Professor

Computer & Information Science

92.034 alumnos

4 cursos

Ofrecido por

Universidad de Pensilvania

Comienza a trabajar para obtener tu maestría

Este curso es parte del Master of Computer and Information Technology completamente en línea de Universidad de Pensilvania. Si te aceptan en el programa completo, tus cursos cuentan para tu título de grado.

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Programa - Qué aprenderás en este curso

Calificación del contenido87%(5,456 calificaciones)

Semana

Semana 1

3 horas para completar

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 completar

6 videos (Total 44 minutos)

Semana

Semana 2

4 horas para completar

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 completar

7 videos (Total 69 minutos)

Semana

Semana 3

4 horas para completar

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 completar

6 videos (Total 46 minutos)

6 videos

3.1 A History of the Computer7m

3.2 Intro to the von Neumann Architecture8m

3.3 von Neumann Architecture Data6m

3.4 von Neumann Architecture Control Flow5m

3.5 Expressing Algorithms in Pseudocode8m

3.6 Case Studies10m

5 ejercicios de práctica

3.1 A History of the Computer10m

3.2 Intro to the von Neumann Architecture10m

3.3 von Neumann Architecture Data10m

3.4 von Neumann Architecture Control Flow10m

3.5 Expressing Algorithms in Pseudocode10m

Semana

Semana 4

7 horas para completar

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 completar

9 videos (Total 91 minutos), 12 lecturas, 12 cuestionarios

9 videos

4.1 Introduction to Python6m

4.2 Variables13m

4.3 Conditional Statements8m

4.4 Lists7m

4.5 Iteration14m

4.6 Functions10m

4.7 Classes and Objects9m

4.8 Case Studies11m

4.9 Course Conclusion8m

12 lecturas

Programming on the Coursera Platform10m

Python Playground

Variables Programming Activity20m

Solution to Variables Programming Activity10m

Conditionals Programming Activity20m

Solution to Conditionals Programming Activity10m

Solution to Lists Programming Assignment5m

Solution to Loops Programming Assignment10m

Solution to Functions Programming Assignment10m

Solution to Challenge Programming Assignment10m

Solution to Classes and Objects Programming Assignment10m

Solution to Project Part 410m

12 ejercicios de práctica

4.2 Variables10m

4.3 Conditional Statements5m

4.4 Lists10m

Lists Programming Assignment15m

4.5 Iteration10m

Loops Programming Assignment30m

4.6 Functions10m

Functions Programming Assignment20m

(Optional) Challenge Programming Assignment20m

4.7 Classes and Objects10m

Classes and Objects Programming Assignment20m

Project Part 4: Implementing the Solution in Python25m

Reseñas

4.7

422 reseña

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

Principales reseñas sobre COMPUTATIONAL THINKING FOR PROBLEM SOLVING

por MS4 de may. 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 BM14 de feb. de 2019

Thoroughly enjoyed the course. If you are new to computer science or need a refresher of the basic concepts you learned in high school / college, this is the perfect course

por NA14 de ene. 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 GB30 de sep. de 2019

Very well thought out. This course covers simple concepts while still being engaging and challenging. Examples from varying disciplines help illustrate concepts in a real-life context.

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Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si compro el Certificado?
Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.
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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Habilidades que obtendrás