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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.

立即開始，按照自己的計劃學習。

根據您的日程表重置截止日期。

建議：4 weeks, 6-8 hours/week...

字幕：英語（English）

立即開始，按照自己的計劃學習。

根據您的日程表重置截止日期。

建議：4 weeks, 6-8 hours/week...

字幕：英語（English）

週

1Computational 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....

6 個視頻 （總計 44 分鐘）, 6 個測驗

1.2 Decomposition6分鐘

1.3 Pattern Recognition5分鐘

1.4 Data Representation and Abstraction7分鐘

1.5 Algorithms8分鐘

1.6 Case Studies11分鐘

1.2 Decomposition10分鐘

1.3 Pattern Recognition10分鐘

1.4 Data Representation and Abstraction15分鐘

1.5 Algorithms15分鐘

週

2When 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....

7 個視頻 （總計 69 分鐘）, 10 個測驗

2.2 Linear Search5分鐘

2.3 Algorithmic Complexity8分鐘

2.4 Binary Search11分鐘

2.5 Brute Force Algorithms13分鐘

2.6 Greedy Algorithms9分鐘

2.7 Case Studies12分鐘

2.1 Finding the Largest Value10分鐘

2.2 Linear Search10分鐘

2.3 Algorithmic Complexity10分鐘

2.4 Binary Search10分鐘

2.5 Brute Force Algorithms15分鐘

2.6 Greedy Algorithms10分鐘

週

3Computational 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....

6 個視頻 （總計 46 分鐘）, 10 個測驗

3.2 Intro to the von Neumann Architecture8分鐘

3.3 von Neumann Architecture Data6分鐘

3.4 von Neumann Architecture Control Flow5分鐘

3.5 Expressing Algorithms in Pseudocode8分鐘

3.6 Case Studies10分鐘

3.1 A History of the Computer10分鐘

3.2 Intro to the von Neumann Architecture10分鐘

3.3 von Neumann Architecture Data10分鐘

3.4 von Neumann Architecture Control Flow10分鐘

3.5 Expressing Algorithms in Pseudocode10分鐘

週

4Writing 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....

9 個視頻 （總計 91 分鐘）, 12 個閱讀材料, 12 個測驗

4.2 Variables13分鐘

4.3 Conditional Statements8分鐘

4.4 Lists7分鐘

4.5 Iteration14分鐘

4.6 Functions10分鐘

4.7 Classes and Objects9分鐘

4.8 Case Studies11分鐘

4.9 Course Conclusion8分鐘

Programming on the Coursera Platform10分鐘

Python Playground

Variables Programming Activity20分鐘

Solution to Variables Programming Activity10分鐘

Conditionals Programming Activity20分鐘

Solution to Conditionals Programming Activity10分鐘

Solution to Lists Programming Assignment5分鐘

Solution to Loops Programming Assignment10分鐘

Solution to Functions Programming Assignment10分鐘

Solution to Challenge Programming Assignment10分鐘

Solution to Classes and Objects Programming Assignment10分鐘

Solution to Project Part 410分鐘

4.2 Variables10分鐘

4.3 Conditional Statements5分鐘

4.4 Lists10分鐘

Lists Programming Assignment15分鐘

4.5 Iteration10分鐘

Loops Programming Assignment30分鐘

4.6 Functions10分鐘

Functions Programming Assignment20分鐘

(Optional) Challenge Programming Assignment20分鐘

4.7 Classes and Objects10分鐘

Classes and Objects Programming Assignment20分鐘

Project Part 4: Implementing the Solution in Python25分鐘

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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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. This is a useful predictor of success in the Master of Computer and Information Technology program at the University of Pennsylvania, which is offered both on-campus and online. In this course you will learn from MCIT instructors and become familiar with the quality and style of MCIT Online courses.

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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