| Neuroscience (DR) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
| Course Code: | SBY6008 | ||||
| Course Name: | Programming | ||||
| Semester: | Spring | ||||
| Course Credits: |
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| Language of instruction: | Turkish | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Departmental Elective | ||||
| Course Level: |
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| Mode of Delivery: | Face to face | ||||
| Course Coordinator: | Dr. Öğr. Üy. GÖKÇER ESKİKURT | ||||
| Course Lecturer(s): | Asst. Prof. Gökçer Eskikurt | ||||
| Course Assistants: |
| Course Objectives: | This course introduces the C Programming Language and aims to give an overview of the language. Basic and advanced features of the language are covered through programming assignments. Through lectures and assignments, students are expected to acquire a good command of the C programming language. |
| Course Content: | In this course, expressions, selection statements, loops, arrays, functions and basic data types in C programming language will be examined. |
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The students who have succeeded in this course;
1) can define the basic data types in C programming language 2) can explain input and output functions in C programming language 3) Use selection expressions such as if, switch in the program 4) can use while and for loop expressions in the program 5) Design the data structures required for program using arrays 6) Design a program using functions |
| Week | Subject | Related Preparation |
| 1) | Introduction to basic programming with R | - |
| 2) | Description of variable types | - |
| 3) | Data types | - |
| 4) | The use of conditional statements and loops | - |
| 5) | Writing up functions and calling funcitons | - |
| 6) | Introduction to experiment programming with E-Prime | - |
| 7) | Introduction to experiment programming with PsychoPy | - |
| 8) | Midterm Assignment | - |
| 9) | Introduction to data analysis with R | - |
| 10) | T-test and ANOVA | - |
| 11) | Correlation and Regression | - |
| 12) | Non-parametric tests | - |
| 13) | Linear Mixed Effect Models and Generalized Linear Mixed Effect Models Analyses | - |
| 14) | Data visualization | - |
| Course Notes / Textbooks: | The Book of R: A First Course in Programming and Statistics Tilman M. Davies |
| References: | The Book of R: A First Course in Programming and Statistics Tilman M. Davies |
| Course Learning Outcomes | 1 |
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| Program Outcomes | ||||||||
| 1) 1) To be able to define the basic concepts of neuroscience, understand and express neurophysiological functions of brain and neuroanatomical structures, functional organization of central nervous system and basic principles of normal functioning. | ||||||||
| 2) 2) To have theoretical knowledge about etiopathogenesis of neurological and psychiatric diseases and to have knowledge of neurological and cognitive impairments and central nervous system pathology knowledge in these diseases. | ||||||||
| 3) 1) To be able to have basic theoretical knowledge about transcranial neuromodulation methods and to use these methods in the field of study, such as radiological and electrophysiological research and investigation methods used in neurological and psychiatric diseases such as electronomyfromography, electroencephalography, evoked potentials and neuroimaging methods. | 1 | 1 | 1 | 1 | 1 | 1 | ||
| 4) 1) Ability to work within the team in the field of neuroscience research | ||||||||
| 5) 1) Transcribe and present the findings and research results verbally or in writing | 1 | 1 | 1 | 1 | 1 | 1 | ||
| 6) 1) Ability to use communication and computer technologies efficiently in their work. | 2 | 2 | 2 | 2 | 2 | 2 | ||
| 7) 2) Having a sense of ethical responsibility in research. | ||||||||
| 8) 1) Undertake the responsibility of the task alone and carry out independent work. | 1 | 1 | 1 | 1 | 1 | 1 | ||
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | 1) To be able to define the basic concepts of neuroscience, understand and express neurophysiological functions of brain and neuroanatomical structures, functional organization of central nervous system and basic principles of normal functioning. | |
| 2) | 2) To have theoretical knowledge about etiopathogenesis of neurological and psychiatric diseases and to have knowledge of neurological and cognitive impairments and central nervous system pathology knowledge in these diseases. | |
| 3) | 1) To be able to have basic theoretical knowledge about transcranial neuromodulation methods and to use these methods in the field of study, such as radiological and electrophysiological research and investigation methods used in neurological and psychiatric diseases such as electronomyfromography, electroencephalography, evoked potentials and neuroimaging methods. | |
| 4) | 1) Ability to work within the team in the field of neuroscience research | |
| 5) | 1) Transcribe and present the findings and research results verbally or in writing | 1 |
| 6) | 1) Ability to use communication and computer technologies efficiently in their work. | 2 |
| 7) | 2) Having a sense of ethical responsibility in research. | |
| 8) | 1) Undertake the responsibility of the task alone and carry out independent work. | 1 |
| Semester Requirements | Number of Activities | Level of Contribution |
| Homework Assignments | 2 | % 20 |
| Midterms | 1 | % 30 |
| Final | 1 | % 50 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 50 | |
| PERCENTAGE OF FINAL WORK | % 50 | |
| total | % 100 | |
| Activities | Number of Activities | Workload |
| Course Hours | 16 | 32 |
| Application | 16 | 32 |
| Study Hours Out of Class | 16 | 32 |
| Midterms | 1 | 40 |
| Final | 1 | 60 |
| Total Workload | 196 | |