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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/computational-thinking-problem-solving
课程评论：没有评论
课程名称：计算思维与问题解决 概述：计算思维是一种系统性地解决问题的过程，旨在创建和表达可以由计算机执行的解决方案。无论您来自哪个领域，都可以参与本课程，无需成为计算机科学家！许多定量和数据导向的问题都可以通过计算思维得到解决，掌握计算思维将为您提供解决具有实际社会影响问题的基础。 在本课程中，您将学习计算思维的四个支柱、计算机科学家如何开发和分析算法，以及如何利用Python编程语言在计算机上实现解决方案。完成课程后，您将能够开发一个算法，并通过编写简单的Python程序向计算机表达该算法。 课程大纲： 1. **计算思维的支柱** - 计算思维是一种利用计算机科学概念与思想来解决问题的方法。随着计算在现代社会各个方面的普及，掌握利用计算思维解决现实问题的能力已成为21世纪的一项关键技能。本模块介绍计算思维的四个支柱：分解、模式识别、数据表示与抽象、和算法，并展示它们在问题解决过程中的应用。 2. **表达与分析算法** - 使用计算思维解决问题时，实际上是在开发算法：一系列逐步的指令。本模块将介绍一些常见的算法及自我开发算法的一般方法，帮助您在寻找问题最佳解决方案时能够评估和分析算法的性能。 3. **现代计算机的基本操作** - 在编写程序实现算法之前，我们需要理解计算机的基本功能，包括如何执行指令和使用数据。本模块介绍现代计算机的内部工作原理及其基本操作，并引入一种称为伪代码的表达方式，以帮助您使用编程语言实施解决方案。 4. **使用Python应用计算思维** - 编写程序是计算思维过程的最后一步。本模块将介绍Python编程语言及其核心特性，即使您从未编写过程序，完成本模块后，您也将能够编写简单的Python程序，帮助您将算法表达给计算机，作为问题解决过程的一部分。 通过参与本课程，您将与来自不同职业背景的人士合作，利用计算思维解决问题，并思考如何通过计算思维产生积极的社会影响。
Name:Pillars of Computational Thinking
Description: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. Computational thinking is built on four pillars: decomposition, pattern recognition, data representation and abstraction, and algorithms. This module introduces you to the four pillars of computational thinking and shows how they can be applied as part of the problem solving process.
Name:Expressing and Analyzing Algorithms
Description: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.
Name:Fundamental Operations of a Modern Computer
Description: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.
Name:Applied Computational Thinking Using Python
Description: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.
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.
