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.
Computational Thinking for Problem Solving
Université de PennsylvanieÀ propos de ce cours
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Approx. 17 heures pour terminer
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Sous-titres : Français, Portugais (brésilien), Russe, Anglais, Espagnol
Compétences que vous acquerrez
Simple AlgorithmPython ProgrammingProblem SolvingComputation
Résultats de carrière des étudiants
42%
ont commencé une nouvelle carrière après avoir terminé ce cours
32%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau débutant
Approx. 17 heures pour terminer
Anglais
Sous-titres : Français, Portugais (brésilien), Russe, Anglais, Espagnol
Offert par
Université de Pennsylvanie
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.
Programme du cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
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 heures pour terminer
6 vidéos (Total 44 min)
6 vidéos
1.1 Introduction4 min
1.2 Decomposition6 min
1.3 Pattern Recognition5 min
1.4 Data Representation and Abstraction7 min
1.5 Algorithms8 min
1.6 Case Studies11 min
4 exercices pour s'entraîner
1.2 Decomposition10 min
1.3 Pattern Recognition10 min
1.4 Data Representation and Abstraction15 min
1.5 Algorithms15 min
4 heures pour terminer
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 heures pour terminer
7 vidéos (Total 69 min)
7 vidéos
2.2 Linear Search5 min
2.3 Algorithmic Complexity8 min
2.4 Binary Search11 min
2.5 Brute Force Algorithms13 min
2.6 Greedy Algorithms9 min
2.7 Case Studies12 min
6 exercices pour s'entraîner
2.1 Finding the Largest Value10 min
2.2 Linear Search10 min
2.3 Algorithmic Complexity10 min
2.4 Binary Search10 min
2.5 Brute Force Algorithms15 min
2.6 Greedy Algorithms10 min
4 heures pour terminer
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 heures pour terminer
6 vidéos (Total 46 min)
6 vidéos
3.2 Intro to the von Neumann Architecture8 min
3.3 von Neumann Architecture Data6 min
3.4 von Neumann Architecture Control Flow5 min
3.5 Expressing Algorithms in Pseudocode8 min
3.6 Case Studies10 min
5 exercices pour s'entraîner
3.1 A History of the Computer10 min
3.2 Intro to the von Neumann Architecture10 min
3.3 von Neumann Architecture Data10 min
3.4 von Neumann Architecture Control Flow10 min
3.5 Expressing Algorithms in Pseudocode10 min
7 heures pour terminer
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 heures pour terminer
9 vidéos (Total 91 min), 12 lectures, 12 quiz
9 vidéos
4.2 Variables13 min
4.3 Conditional Statements8 min
4.4 Lists7 min
4.5 Iteration14 min
4.6 Functions10 min
4.7 Classes and Objects9 min
4.8 Case Studies11 min
4.9 Course Conclusion8 min
12 lectures
Programming on the Coursera Platform10 min
Python Playground
Variables Programming Activity20 min
Solution to Variables Programming Activity10 min
Conditionals Programming Activity20 min
Solution to Conditionals Programming Activity10 min
Solution to Lists Programming Assignment5 min
Solution to Loops Programming Assignment10 min
Solution to Functions Programming Assignment10 min
Solution to Challenge Programming Assignment10 min
Solution to Classes and Objects Programming Assignment10 min
Solution to Project Part 410 min
12 exercices pour s'entraîner
4.2 Variables10 min
4.3 Conditional Statements5 min
4.4 Lists10 min
Lists Programming Assignment15 min
4.5 Iteration10 min
Loops Programming Assignment30 min
4.6 Functions10 min
Functions Programming Assignment20 min
(Optional) Challenge Programming Assignment20 min
4.7 Classes and Objects10 min
Classes and Objects Programming Assignment20 min
Project Part 4: Implementing the Solution in Python25 min
Avis
Meilleurs avis pour COMPUTATIONAL THINKING FOR PROBLEM SOLVING
par J18 déc. 2018
Excellent course for beginners with enough depth, programming and computational theory to increase their computer science knowledge to a higher level. It builds a good foundation of how computers work
par DT8 juil. 2020
Very comprehensive course. As a chemist who is interested in doing a course in programming I was quite uncertain if I'd be able to pick it up however this course has helped me understand the basics.
par JR27 juin 2019
The course is great. I learned a lot. The support for the course is SUPER slow. It's hard to get any direct help for any questions or issues that you are having. Beware of assignment 4.7!
par MS4 mai 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
Foire Aux Questions
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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 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/
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.
