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Fundamentals of Computing

Scott Rixner, Joe Warren, Luay Nakhleh, John Greiner, and Stephen Wong

This Specialization covers much of the material that first-year Computer Science students take at Rice University, brought to you by the world-class Faculty who teach our master's and PhD programs. Students learn sophisticated programming skills in Python from the ground up and apply these skills in building more than 20 fun projects. The Specialization concludes with a Capstone exam that allows the students to demonstrate the range of knowledge that they have acquired in the Specialization.

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What's inside

Seven courses

An Introduction to Interactive Programming in Python (Part 1)

(0 hours)

This two-part course introduces the basics of building simple interactive applications using Python. Our language of choice, Python, is easy to learn and used in many computational courses on Coursera. We have developed a new browser-based programming environment that simplifies developing interactive applications in Python. These applications will involve windows with graphical contents that respond to buttons, the keyboard, and the mouse.

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An Introduction to Interactive Programming in Python (Part 2)

(0 hours)

This two-part course is designed for beginners to learn the basics of building simple interactive applications in Python. In part 2, we will introduce more programming elements and use them to create games like Blackjack.

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Principles of Computing (Part 1)

(0 hours)

This two-part course builds upon Python programming skills learned in our Introduction to Interactive Programming in Python course. We will enhance those skills with programming practices and mathematical problem-solving skills that underlie larger-scale computational problem-solving and programming.

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Principles of Computing (Part 2)

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This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language.

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Algorithmic Thinking (Part 1)

(0 hours)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part course builds on the principles learned in our Principles of Computing course and is designed to train students in the mathematical concepts and process of "Algorithmic Thinking," allowing them to build simpler, more efficient solutions to real-world computational problems.

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Algorithmic Thinking (Part 2)

(0 hours)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

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The Fundamentals of Computing Capstone Exam

This capstone exam concludes the Fundamentals of Computing specialization. It allows students to demonstrate their mastery of the material covered in the previous six courses. The exam questions are updated periodically to ensure that students are solving the problems on their own.

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Time

175 hours

Level

Introductory

Via

Coursera

Institution

Rice University

Instructors

Scott Rixner

Joe Warren

Luay Nakhleh

John Greiner

Stephen Wong

Level

Introductory

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