|
|
| ELK2027 | Engineering Software | 2+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of ELECTRICAL and ELECTRONICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Prof. Dr. Gökçe HACIOĞLU | | Co-Lecturer | Assoc. Prof. Dr. Yusuf SEVİM | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The purpose of this course is to provide an introduction to Python programming language. The course covers basic syntax, data types, control structures, functions, and object-oriented programming concepts. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Knowledge of Python fundamentals: Students should have a solid understanding of Python syntax, including variables, data types, operators, and control structures such as loops and conditional statements. They should also be familiar with the concept of functions and how to define and call them. | | 1, | | LO - 2 : | Understanding of object-oriented programming (OOP) principles. | | 1, | | LO - 3 : | Proficiency in writing Python code: Students should be able to write Python code that is clean, well-organized, and follows best practices. They should understand how to use proper indentation, meaningful variable and function names, and clear comments to enhance the readability and maintainability. | | 1, | | LO - 4 : | Ability to solve problems using Python | | 1, | | LO - 5 : | Familiarity with Python libraries and tools: Students should be familiar with commonly used Python libraries and tools for tasks such as data manipulation, analysis, and visualization. They should have hands-on experience with libraries like NumPy, Pandas, and Matplotlib | | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| The course spans over 14 weeks and covers an extensive range of topics. It commences with an introduction to Python and programming concepts, covering syntax and code structure. The course then moves on to numerical computations and libraries that focus on data types, mathematical functions, arrays, matrices and visualization. It also covers signal processing and analysis techniques, including digital signal processing and Fourier analysis. |
| |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | | | | | | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | | | | |
|