Course Detail
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|
PYTHON PROGRAMMING for ENGINEERS | BME3167880 | Fall Semester | 3+0 | 3 | 6 |
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 | Book Chapter 2 |
2 | Functions and External Libraries | Book Chapter 3 |
3 | Lists and Tuples | Book Chapter 10, 12 |
4 | Dictionaries | Book Chapter 11 |
5 | Input/Output and Exceptions | Book Chapter 14 |
6 | Strings and String Manipulation | Book Chapter 8 |
7 | Searching and Sorting | |
8 | Object Oriented Programming: classes, methods, inheritance | Book Chapter 15, 16, 17, 18 |
9 | Simulation and Optimization | |
10 | Numerical Computations and Methods | |
11 | Data Analysis and Visualization | |
12 | Image processing | |
13 | Machine Learning | |
14 | Advanced Applications with Python | |
Resources |
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 | An ability to apply knowledge of mathematics, science, and engineering | | | | | |
2 | An ability to identify, formulate, and solve engineering problems | | | | | X |
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 | An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | | | X |
5 | An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | | | |
6 | An ability to function on multidisciplinary teams | | | | X | |
7 | An ability to communicate effectively | | | | | |
8 | A recognition of the need for, and an ability to engage in life-long learning | | | | | |
9 | An understanding of professional and ethical responsibility | | | | | |
10 | A knowledge of contemporary issues | | | | | |
11 | The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | | | | | |
12 | Capability to apply and decide on engineering principals while understanding and rehabilitating the human body | | | | | |
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 | BME3167880 | Fall Semester | 3+0 | 3 | 6 |
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 | Book Chapter 2 |
2 | Functions and External Libraries | Book Chapter 3 |
3 | Lists and Tuples | Book Chapter 10, 12 |
4 | Dictionaries | Book Chapter 11 |
5 | Input/Output and Exceptions | Book Chapter 14 |
6 | Strings and String Manipulation | Book Chapter 8 |
7 | Searching and Sorting | |
8 | Object Oriented Programming: classes, methods, inheritance | Book Chapter 15, 16, 17, 18 |
9 | Simulation and Optimization | |
10 | Numerical Computations and Methods | |
11 | Data Analysis and Visualization | |
12 | Image processing | |
13 | Machine Learning | |
14 | Advanced Applications with Python | |
Resources |
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 | An ability to apply knowledge of mathematics, science, and engineering | | | | | |
2 | An ability to identify, formulate, and solve engineering problems | | | | | X |
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 | An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | | | X |
5 | An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | | | |
6 | An ability to function on multidisciplinary teams | | | | X | |
7 | An ability to communicate effectively | | | | | |
8 | A recognition of the need for, and an ability to engage in life-long learning | | | | | |
9 | An understanding of professional and ethical responsibility | | | | | |
10 | A knowledge of contemporary issues | | | | | |
11 | The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | | | | | |
12 | Capability to apply and decide on engineering principals while understanding and rehabilitating the human body | | | | | |
Assessment Methods
Contribution Level | Absolute Evaluation |
Rate of Midterm Exam to Success | | 30 |
Rate of Final Exam to Success | | 70 |
Total | | 100 |
Numerical Data
Ekleme Tarihi: 09/10/2023 - 10:40Son Güncelleme Tarihi: 09/10/2023 - 10:41
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