Kocaeli University / European Credit Transfer System (ECTS)

Name of Lecturer(s)

Assistant Prof. Dr. Recep Kaya GÖKTAŞ

Learning Outcomes of the Course Unit
Program Competencies-Learning Outcomes Relation

Learning Outcomes of the Course Unit

1) Develops basic level computer programming knowledge and skills.
2) Develops basic skills to use computer programming as a tool to solve environmental engineering problems.
3) Develops an introductory knowledge of numerical solution techniques.

Program Competencies-Learning Outcomes Relation

		Program Competencies
		1	2	3	4
Learning Outcomes
	1	Middle	High	Middle	No relation
	2	High	High	High	No relation
	3	Middle	Low	No relation	No relation

Mode of Delivery

Face to Face

Prerequisites and Co-Requisites

1) Mathematics I Completing the following course succesfully:

Recommended Optional Programme Components

Mathematics I Mathematics II Physics I Physics II Engineering Mathematics Linear Algebra

Course Contents

Introduction to computer programming. Introduction to the Python language. Variables and basic data structures. Functions. Branching statements. Iteration. Recursion. Object-oriented programming. Good programming practices. Debugging. Reading and writing data. Visualization and plotting. Parallel computing. Introduction to numerical methods.

Weekly Schedule

1) Introduction to computers and programming. Python Basics.
2) Variables and basic data structures.
3) Functions.
4) Branching statements.
5) Iteration.
6) Recursion.
7) Object-oriented programming.
8) Midterm Exam.
9) Complexity.
10) Representation of numbers.
11) Good programming practices and debugging.
12) Reading and writing data.
13) Visualization and plotting.
14) Numerical programming.
15) Numerical programming.
16) Final Exam.

Recommended or Required Reading

1- “A Primer on Scientific Programming with Python, 2nd Edition” by Hans Petter Langtangen. Springer.
2- “Python Programming for the Absolute Beginner, 3rd Edition” by Michael Dawson. (2010). Course Technology, Cengage Learning (available at the KOÜ Library in electronic format)
3- “Python for Informatics: Exploring Information” by Charles Severance. (available free online at http://www.pythonlearn.com/book.php)
4- “Think Python: How to Think Like a Computer Scientist” by Allen B. Downey. Green Tea Press. (available online under the GNU Free Documentation License)
5- “Beginning Python®: Using Python 2.6 and Python 3.1” by James Payne. 2010. Wrox. (available at the KOÜ Library in electronic format)
6- “Python Programming: An Introduction to Computer Science” 2nd Ed. by John M. Zelle. 2010. Franklin, Beedle and Associates Inc. (available at the KOÜ library)
7- “Non-Programmer's Tutorial for Python 3”. (Wikibooks)

Planned Learning Activities and Teaching Methods

1) Lecture
2) Drill and Practice
3) Demonstration
4) Group Study
5) Case Study
6) Lab / Workshop
7) Self Study
8) Problem Solving
9) Project Based Learning

Assessment Methods and Criteria

Contribution of Semester Studies to Course Grade

70%

		Number	Percentage
Semester Studies	Midterm Examination	1	30%
	Quiz	2	30%
	Laboratory	1	15%
	Project	1	15%
	Other(s)	1	10%

Contribution of Final Examination to Course Grade

30%

Total

100%

Language of Instruction

English

Work Placement(s)

Not Required

Course Unit Title	Course Unit Code	Type of Course Unit	Level of Course Unit	Year of Study	Semester	ECTS Credits
Computer Programming	CEV208	Compulsory	Bachelor's degree	2	Spring	5