Information Systems Engineering
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

FET210

Ders İsmi:

Programming with Python

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Laboratory	ECTS
2	1	0	5

Language of instruction:

Turkish

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Course Coordinator :

Assoc. Prof. Dr. CEVAT RAHEBİ

Course Lecturer(s):

Asst. Prof. Dr. ALİYE SARAÇ
Asst. Prof. Dr. BUKET İŞLER

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:

The aim of the course is to provide students with programming experience and to introduce computer-based techniques used in bioengineering.

Course Content:

This course introduces the fundamentals of using the Python language in artificial intelligence applications and introduces basic artificial intelligence problems. It begins with an introduction to the basics of the Python language. In this section, python language rules will be explained to students and will focus on the analysis of biological data using python. Next, next generation sequencing data, evolutionary kinship analysis, introduction of artificial intelligence problems such as single nucleotide polymorphism and copy number polymorphism detection will be discussed.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) 1. Students who successfully complete this course; 2. Able to program in Python language 3. Will be able to explain problems and process data analysis in basic Python program 4. Will be able to debug Python code 5. Will be able to list the algorithms used in the field of artificial intelligence
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Sources

Course Notes / Textbooks:	1. Lutz, Mark. Programming python. " O'Reilly Media, Inc.", 2001. 2. Zelle, John M. Python programming: an introduction to computer science. Franklin, Beedle & Associates, Inc., 2004.
References:	1. Lutz, Mark. Programming python. " O'Reilly Media, Inc.", 2001. 2. Zelle, John M. Python programming: an introduction to computer science. Franklin, Beedle & Associates, Inc., 2004.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1
Program Outcomes

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

Program Outcomes

Level of Contribution

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
total		%

Week	Subject	Related Preparation
1)	Introduction to programming and python	Introduction to programming and python
2)	Variables, data types, operators, return function, if/else block	Variables, data types, operators, return function, if/else block
3)	Module loading, Module functions, Declarations	Module loading, Module functions, Declarations
4)	List, dict, tuple types, user input, comment block	List, dict, tuple types, user input, comment block
5)	For, while loop, break, continue and iterators	For, while loop, break, continue and iterators
6)	Time, sys, os modules, file read and write	Time, sys, os modules, file read and write
7)	Classes. Regular expressions and regex module	Classes. Regular expressions and regex module
8)	midterm exam
9)	Numpy, scipy, and panda modules. Matrices and sparse matrices	Numpy, scipy, and panda modules. Matrices and sparse matrices
10)	Matplotlib module, K-means clustering and Hierarchical clustering	Matplotlib module, K-means clustering and Hierarchical clustering
11)	python module, one-to-one alignment. Communication with NCBI	python module, one-to-one alignment. Communication with NCBI
12)	Introduction to next generation sequencing analysis, single nucleotide polymorphism, copy number polymorphism	Introduction to next generation sequencing analysis, single nucleotide polymorphism, copy number polymorphism
13)	Multiple sequence alignment and evolutionary tree generation	Multiple sequence alignment and evolutionary tree generation
14)	Application project	Application project
15)	Application project	Application project
16)	final exam