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
宾夕法尼亚大学课程信息
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完成时间大约为18 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
您将获得的技能
- Simple Algorithm
- Python Programming
- Problem Solving
- Computation
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
初级
完成时间大约为18 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
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宾夕法尼亚大学
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.
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完成时间为 3 小时
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.
完成时间为 3 小时
6 个视频 （总计 44 分钟）
完成时间为 4 小时
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.
完成时间为 4 小时
7 个视频 （总计 69 分钟）
完成时间为 4 小时
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.
完成时间为 4 小时
6 个视频 （总计 46 分钟）
完成时间为 7 小时
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.
完成时间为 7 小时
9 个视频 （总计 91 分钟）, 12 个阅读材料, 12 个测验
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- 5 stars80.58%
- 4 stars12.65%
- 3 stars3.29%
- 2 stars1.29%
- 1 star2.16%
来自COMPUTATIONAL THINKING FOR PROBLEM SOLVING的热门评论
由 DA 提供Nov 17, 2018
An excellent bridge into introductory computer science topics. Professors Susan Davidson and Chris Murphy exposed learners to computer science concepts within everyday problems.
由 QT 提供Mar 3, 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.
由 JK 提供Jun 30, 2020
Prior basic python knowledge will help with this course. Instructors were great. However the last week and its assignments need to tie in better with the overall course.
由 JL 提供Feb 8, 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)
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