The course presents programming principles and applications in Python. The topics covered include: Python programming language, use of external libraries, lists and dictionaries, recursion, sorting algorithms, dynamic programming, exception handling, input/output. The course presents applications from different fields of engineering and computer science: simulation, optimization, data analysis, data visualization, image processing, machine learning and more.
Course Content
This course contains; Introduction to Python: Variables and Memory, Strings, Conditionals, Flow Control,Functions and External Libraries,Lists and Tuples,Dictionaries,Input/Output and Exceptions,Strings and String Manipulation,Searching and Sorting ,Object Oriented Programming: classes, methods, inheritance ,Simulation and Optimization,Numerical Computations and Methods,Data Analysis and Visualization,Image processing ,Machine Learning,Advanced Applications with Python.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
İmplement algorithms in Python programming language
12, 2, 21, 6, 9
A, E, F
Acquire the object oriented programming skill in Python
12, 2, 21, 6, 9
A, E, F
Use the code libraries that are available for different applications
2, 6, 9
E, F
Code the solutions in Python for basic problems of optimization, image processing and machine learning
12, 2, 21, 6, 9
A, E, F
Acquire the ability to analyze and visualize data in Python
12, 21, 6, 9
A, E, F
Teaching Methods:
12: Problem Solving Method, 2: Project Based Learning Model, 21: Simulation Technique, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:
A: Traditional Written Exam, E: Homework, F: Project Task
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Python: Variables and Memory, Strings, Conditionals, Flow Control
Course Textbook:
Think Python, How to Think Like a Computer Scientist, Allen Downey
http://www.cs.tau.ac.il/courses/pyProg/1213a/misc/thinkpython.pdf
Supplementary Material:
Dive Into Python, Mark Pilgrim
http://www.cs.tau.ac.il/courses/pyProg/1213a/misc/diveintopython.pdf
Learn Python the Hard Way, 3rd ed., Zed A. Shaw
ISBN-13: 978-0321884916
Python web page: https://www.python.org
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
1. An ability to apply knowledge of mathematics, science, and engineering
2
2. An ability to identify, formulate, and solve engineering problems
X
3
3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
X
4
4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
X
5
5. An ability to design and conduct experiments, as well as to analyze and interpret data
6
6. An ability to function on multidisciplinary teams
X
7
7. An ability to communicate effectively
8
8. A recognition of the need for, and an ability to engage in life-long learning
9
9. An understanding of professional and ethical responsibility
10
10. A knowledge of contemporary issues
11
11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
30
Rate of Final Exam to Success
70
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
14
3
42
Guided Problem Solving
0
0
0
Resolution of Homework Problems and Submission as a Report
6
10
60
Term Project
14
2
28
Presentation of Project / Seminar
0
0
0
Quiz
0
0
0
Midterm Exam
1
20
20
General Exam
1
30
30
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
180
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(180/30)
6
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.
Detail Informations of the Course
Course Description
Course
Code
Semester
T+P (Hour)
Credit
ECTS
PYTHON PROGRAMMING for ENGINEERS
-
Fall Semester
3+0
3
6
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of Course
English
Course Level
First Cycle (Bachelor's Degree)
Course Type
Elective
Course Coordinator
Prof.Dr. Bahadır Kürşat GÜNTÜRK
Name of Lecturer(s)
Prof.Dr. Bahadır Kürşat GÜNTÜRK
Assistant(s)
Aim
The course presents programming principles and applications in Python. The topics covered include: Python programming language, use of external libraries, lists and dictionaries, recursion, sorting algorithms, dynamic programming, exception handling, input/output. The course presents applications from different fields of engineering and computer science: simulation, optimization, data analysis, data visualization, image processing, machine learning and more.
Course Content
This course contains; Introduction to Python: Variables and Memory, Strings, Conditionals, Flow Control,Functions and External Libraries,Lists and Tuples,Dictionaries,Input/Output and Exceptions,Strings and String Manipulation,Searching and Sorting ,Object Oriented Programming: classes, methods, inheritance ,Simulation and Optimization,Numerical Computations and Methods,Data Analysis and Visualization,Image processing ,Machine Learning,Advanced Applications with Python.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
İmplement algorithms in Python programming language
12, 2, 21, 6, 9
A, E, F
Acquire the object oriented programming skill in Python
12, 2, 21, 6, 9
A, E, F
Use the code libraries that are available for different applications
2, 6, 9
E, F
Code the solutions in Python for basic problems of optimization, image processing and machine learning
12, 2, 21, 6, 9
A, E, F
Acquire the ability to analyze and visualize data in Python
12, 21, 6, 9
A, E, F
Teaching Methods:
12: Problem Solving Method, 2: Project Based Learning Model, 21: Simulation Technique, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:
A: Traditional Written Exam, E: Homework, F: Project Task
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Python: Variables and Memory, Strings, Conditionals, Flow Control
Course Textbook:
Think Python, How to Think Like a Computer Scientist, Allen Downey
http://www.cs.tau.ac.il/courses/pyProg/1213a/misc/thinkpython.pdf
Supplementary Material:
Dive Into Python, Mark Pilgrim
http://www.cs.tau.ac.il/courses/pyProg/1213a/misc/diveintopython.pdf
Learn Python the Hard Way, 3rd ed., Zed A. Shaw
ISBN-13: 978-0321884916
Python web page: https://www.python.org
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
1. An ability to apply knowledge of mathematics, science, and engineering
2
2. An ability to identify, formulate, and solve engineering problems
X
3
3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
X
4
4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
X
5
5. An ability to design and conduct experiments, as well as to analyze and interpret data
6
6. An ability to function on multidisciplinary teams
X
7
7. An ability to communicate effectively
8
8. A recognition of the need for, and an ability to engage in life-long learning
9
9. An understanding of professional and ethical responsibility
10
10. A knowledge of contemporary issues
11
11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context
