Information Package / Course Catalogue
Python Programming and Engineering Applications
Course Code: EE216
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: English
Work Placement: N/A
Theory: 2
Prt.: 2
Credit: 3
Lab: 0
ECTS: 3
Objectives of the Course

The objective of the course is to teach Python programming language to students who have basic computer and calculus knowledge and to enable them to write computer programs related to basic engineering subjects. In this context, the basic structure of the Python programming language will be given, various programming examples will be shown, and usage of them in computer will be discussed.

Course Content

Variables, strings, conditionals, flow Control, operators in Python, input-output operations, user defined functions, arrays, loops, data analysis and visualization

Name of Lecturer(s)
Learning Outcomes
1.To gain code writing skill in Python
2.To understand the logic of using arrays and the other data structures in Python
3.To understand the logic of using selection structures, loops, and functions in Python
4.To understand Python programming applications including various engineering topics.
5.To learn data analysis and visualization in Python
Recommended or Required Reading
1.Guttag, John. Introduction to Computation and Programming Using Python: With Application to Understanding Data. Second Edition. MIT Press, 2016
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Python, installation of Python
Week 2 - Theoretical
Constants, variables, arithmetic operations and expressions in Python
Week 3 - Theoretical
Arithmetic, relational, and logical operators, and cases
Week 4 - Theoretical
Flow control with selection structures
Week 5 - Theoretical
Python Loops
Week 6 - Theoretical
User-controlled input-output operations and applications
Week 7 - Theoretical
Lists, Arrays, sets, and tupples
Week 8 - Theoretical
Numpy library and linear algebra applications
Week 9 - Theoretical
User defined functions
Week 10 - Theoretical
Clusters, dictionaries and databases
Week 11 - Theoretical
Scilearn and Pandas library and applications
Week 12 - Theoretical
Keras library and applications
Week 13 - Theoretical
Data analysis and visualization
Week 14 - Theoretical
Applications
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures14%5
Assignment5%15
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140228
Assignment51110
Midterm Examination1224
Final Examination1426
TOTAL WORKLOAD (hours)76
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
OÇ-1
4
5
5
5
5
5
3
3
4
4
5
OÇ-2
4
5
5
5
5
5
3
3
4
4
5
OÇ-3
4
5
5
5
5
5
3
3
4
4
5
OÇ-4
4
5
5
5
5
5
3
3
4
4
5
OÇ-5
5
5
5
5
5
4
3
3
4
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026