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Principles of Computing (Part 2)

Offered By: Rice University via Coursera

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Algorithms and Data Structures Courses Python Courses Sorting Algorithms Courses Searching Algorithms Courses Algorithmic Thinking Courses Recursion Courses

Course Description

Overview

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of 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. The main focus of the class will be weekly mini-projects that build upon the mathematical and programming principles that are taught in the class. To keep the class fun and engaging, many of the projects will involve working with strategy-based games. In part 2 of this course, the programming portion of the class will focus on concepts such as recursion, assertions, and invariants. The mathematical portion of the class will focus on searching, sorting, and recursive data structures. Upon completing this course, you will have a solid foundation in the principles of computation and programming. This will prepare you for the next course in the specialization, which will begin to introduce a structured approach to developing and analyzing algorithms. Developing such algorithmic thinking skills will be critical to writing large scale software and solving real world computational problems.

Syllabus

  • Searching and Data Structures
    • This week, we will explain the importance of searching. We will also explore various data structures and learn about inheritance.
  • Recursion
    • This week, we will explain the importance of recursion.
  • Trees
    • This week, we will explain the importance of trees. We will also explore how to set up game trees so that we can efficiently search them.
  • Modeling, Assertions, and Invariants
    • This week, we will explain the importance of modeling. We will also explore how to use assertions and invariants to ensure that our models are always consistent and correct.

Taught by

Scott Rixner, Joe Warren and Luay Nakhleh

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