University of Pennsylvania
Computational Thinking for Problem Solving
University of Pennsylvania

Computational Thinking for Problem Solving

Taught in English

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112,655 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Susan Davidson

Instructor: Susan Davidson

4.7

(1,356 reviews)

Beginner level
No prior experience required
17 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
Prepare for a degree

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Assessments

27 quizzes

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There are 4 modules in this course

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.

What's included

6 videos4 quizzes2 peer reviews4 discussion prompts

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.

What's included

7 videos6 quizzes4 peer reviews

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.

What's included

6 videos5 quizzes5 peer reviews

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.

What's included

9 videos12 readings12 quizzes

Instructor

Instructor ratings
4.8 (413 ratings)
Susan Davidson
University of Pennsylvania
4 Courses112,947 learners

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Recommended if you're interested in Algorithms

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4.7

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