Introduction to Computer Science for Non-Computer Science Majors - Einzelansicht

LEARNING OBJECTIVES

Course participants will gain an overview of basic data structures and algorithms to solve problems in computer science and become familiar with the Python programming language. Through hands-on assignments, students will get an opportunity to gain a deeper understanding of the topics addressed in the lecture.

Through lectures, exercises and individual work, students will train their ability to:

• analyze a given problem from a computing point of view;
• choose appropriate data structures and algorithm for solving the problem;
• implement their solution using Python;
• deal with errors using online sources;
• prepare a documentation for the software developed;

By successfully completing the course, participants will acquire the knowledge and the skills required to successfully complete various forms of computer-science-related projects.

COURSE CONTENT DESCRIPTION

Theoretical Foundations

• What is an algorithm
• Complexity of algorithms
• Mathematical logic
• Set theory
• Data types and encoding

Linear Data Structures

• Queue and stack
• Array and list
• Set and hash
• Searching and sorting in linear structures

Trees

• General trees
• Binary trees
• Searching and sorting in trees
• Modifications of binary trees

Graphs

• Terminology and properties
• Searching
• Finding optimal paths
• Finding minimum spanning trees
• Optimal matching

Python Programming Language

• Introduction, keywords, flow control
• Data types and structures
• Implementation of the algorithms mentioned above

• Steven S. Skiena: The algorithm design manual. New York: Springer, 1998. ISBN 0387948600.
• Thomas H. Cormen, Charles E. Leiserson a Ronald L. Rivest. Introduction to algorithms. Cambridge: MIT Press, 1989. ISBN 0070131430. 
• Thomas Foster: Logic, Induction and Sets. Cambridge University Press, 2003. ISBN 0-521-82621-7.
• Al Sweigart: Automate the Boring Stuff with Python. Available online from https://automatetheboringstuff.com/
• John Zelle: Python Programming: An Introduction to Computer Science. Franklin, Beedle & Associates Inc. (2003). ISBN 978-1887902991
• Peter Wentworth, Jeffrey Elkner, Allen B. Downey, and Chris Meyers: How to Think Like a Computer Scientist: Learning with Python 3. Available online from http://openbookproject.net/thinkcs/python/english3e/
• Brad Miller and Runestone contributors: Interactive Python: http://interactivepython.org/runestone/default/user/login?_next=/runestone/default/index
• Python documentation: https://www.python.org/doc/

ROOM 

The lecture and exercise ssessions take part in room FC 0.10 (IT Cluster Lab).

To successfully complete the course, students will be required to

• Submit solutions for assignments
• Pass a written or oral test