Treffer: Applied Computational Thinking with Python: Design Algorithmic Solutions for Complex and Challenging Real-World Problems.

Description based upon print version of record. ; Applied Computational Thinking with Python provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time. Developers working with Python will be able to put their knowledge to work with this practical guide using the computational thinking method for problem-solving. ; Cover -- Title Page -- Copyright and Credits -- Dedicated -- About Packt -- Contributors -- Table of Contents -- Preface -- Section 1: Introduction to Computational Thinking -- Chapter 1: Fundamentals of Computer Science -- Technical requirements -- Introduction to computer science -- Learning about computers and the binary system -- Understanding theoretical computer science -- Algorithms -- Coding theory -- Computational biology -- Data structures -- Information theory -- Automata theory -- Formal language theory -- Symbolic computation -- Computational geometry ; Computational number theory -- Learning about a system's software -- Operating systems -- Application software -- Understanding computing -- Architecture -- Programming languages -- Learning about data types and structures -- Data types -- Data structures -- Summary -- Chapter 2: Elements of Computational Thinking -- Technical requirements -- Understanding computational thinking -- Problem 1 -- Conditions -- Decomposing problems -- Recognizing patterns -- Problem 2 -- Mathematical algorithms and generalization -- Generalizing patterns -- Designing algorithms -- Additional problems ; Problem 2 -- Children's soccer party -- Problem 3 -- Savings and interest -- Summary -- Chapter 3: Understanding Algorithms and Algorithmic Thinking -- Technical requirements -- Defining algorithms in depth -- Algorithms should be clear and unambiguous -- Algorithms should have inputs and outputs that are well defined -- Algorithms should have finiteness -- Algorithms have to be feasible -- Algorithms are language-independent -- Designing algorithms -- Problem 1 -- An office lunch -- ...