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Susan Davidson

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Part of the Master of Computer and Information Technology degree
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Computational Thinking for Problem Solving

University of Pennsylvania

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Beginner Level

Approx. 18 hours to complete

English

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Skills you will gain

Simple Algorithm
Python Programming
Problem Solving
Computation

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Beginner Level

Approx. 18 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.84/5 (374 Ratings)

Susan Davidson

Weiss Professor

Computer & Information Science

91,851 Learners

4 Courses

Offered by

University of Pennsylvania

Start working towards your Master's degree

This course is part of the 100% online Master of Computer and Information Technology from University of Pennsylvania. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Content Rating87%(5,438 ratings)

Week

Week 1

3 hours to complete

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 hours to complete

6 videos (Total 44 min)

Week

Week 2

4 hours to complete

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 hours to complete

7 videos (Total 69 min)

Week

Week 3

4 hours to complete

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 hours to complete

6 videos (Total 46 min)

6 videos

3.1 A History of the Computer7m

3.2 Intro to the von Neumann Architecture8m

3.3 von Neumann Architecture Data6m

3.4 von Neumann Architecture Control Flow5m

3.5 Expressing Algorithms in Pseudocode8m

3.6 Case Studies10m

5 practice exercises

3.1 A History of the Computer10m

3.2 Intro to the von Neumann Architecture10m

3.3 von Neumann Architecture Data10m

3.4 von Neumann Architecture Control Flow10m

3.5 Expressing Algorithms in Pseudocode10m

Week

Week 4

7 hours to complete

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 hours to complete

9 videos (Total 91 min), 12 readings, 12 quizzes

9 videos

4.1 Introduction to Python6m

4.2 Variables13m

4.3 Conditional Statements8m

4.4 Lists7m

4.5 Iteration14m

4.6 Functions10m

4.7 Classes and Objects9m

4.8 Case Studies11m

4.9 Course Conclusion8m

12 readings

Programming on the Coursera Platform10m

Python Playground

Variables Programming Activity20m

Solution to Variables Programming Activity10m

Conditionals Programming Activity20m

Solution to Conditionals Programming Activity10m

Solution to Lists Programming Assignment5m

Solution to Loops Programming Assignment10m

Solution to Functions Programming Assignment10m

Solution to Challenge Programming Assignment10m

Solution to Classes and Objects Programming Assignment10m

Solution to Project Part 410m

12 practice exercises

4.2 Variables10m

4.3 Conditional Statements5m

4.4 Lists10m

Lists Programming Assignment15m

4.5 Iteration10m

Loops Programming Assignment30m

4.6 Functions10m

Functions Programming Assignment20m

(Optional) Challenge Programming Assignment20m

4.7 Classes and Objects10m

Classes and Objects Programming Assignment20m

Project Part 4: Implementing the Solution in Python25m

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Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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/

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Computational Thinking for Problem Solving

Computational Thinking for Problem Solving

About this Course

Skills you will gain