School/Faculty/Institute | Graduate School | ||||
Course Code | ITC 544 | ||||
Course Title in English | Cases in Information Technologies and Computing | ||||
Course Title in Turkish | Cases in Information Technologies and Computing | ||||
Language of Instruction | EN | ||||
Type of Course | Exercise,Laboratory Work,Lecture | ||||
Level of Course | Intermediate | ||||
Semester | Summer School | ||||
Contact Hours per Week |
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Estimated Student Workload | 174 hours per semester | ||||
Number of Credits | 7.5 ECTS | ||||
Grading Mode | Standard Letter Grade | ||||
Pre-requisites | None | ||||
Expected Prior Knowledge | Basic machine learning knowledge | ||||
Co-requisites | None | ||||
Registration Restrictions | Graduate Students Only | ||||
Overall Educational Objective | To learn and evaluate the different cases in Information Technologies related to a wide range of applications from user experience to brain technologies. | ||||
Course Description | The aim of the course is to give the fundamental applications in ITC and to enable students to analyze the presented cases. | ||||
Course Description in Turkish | Bu dersin amacı Bilgi Teknolojileri konusundaki vakaları öğrenmek ve değrlendirmektir. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) Learn and discuss fundamental concepts in ITC 2) Analyze and evaluate the cases in ITC 3) Develop a project proposal related to ITC |
Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 |
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1) An ability to develop and deepen their knowledge in the field of Information Technologies at the level of expertise based on their undergraduate level qualifications. | |||
2) An ability to apply scientific and practical knowledge in statistics, computing and computer science. | |||
3) A Comprehensive knowledge of analysis and modeling methods and their limitations. | |||
4) An ability to design and apply analytical, modeling and experimental H 2 based researches, analyzes and interprets complex situations encountered in this process. | |||
5) An ability to transmit the process and results of the work of information systems systematically and clearly in written and oral form in national and international environments. | |||
6) An understanding of data collection, processing, use, interpretation and social, scientific and ethical values in all professional and professional activities. | |||
7) An ability to take a leadership position in multi-disciplinary teams, develop information-based solution approaches in complex situations and to take responsibility. | |||
8) An understanding of the impact of engineering solutions in a global, economic, environmental, and societal context. | |||
9) An ability to communicate verbally and in writing in English at least at the level of B2 of CEFR. | |||
10) An understanding the social and environmental aspects of IT applications. |
N None | S Supportive | H Highly Related |
Program Outcomes and Competences | Level | Assessed by | |
1) | An ability to develop and deepen their knowledge in the field of Information Technologies at the level of expertise based on their undergraduate level qualifications. | N | |
2) | An ability to apply scientific and practical knowledge in statistics, computing and computer science. | N | |
3) | A Comprehensive knowledge of analysis and modeling methods and their limitations. | N | |
4) | An ability to design and apply analytical, modeling and experimental H 2 based researches, analyzes and interprets complex situations encountered in this process. | N | |
5) | An ability to transmit the process and results of the work of information systems systematically and clearly in written and oral form in national and international environments. | N | |
6) | An understanding of data collection, processing, use, interpretation and social, scientific and ethical values in all professional and professional activities. | N | |
7) | An ability to take a leadership position in multi-disciplinary teams, develop information-based solution approaches in complex situations and to take responsibility. | N | |
8) | An understanding of the impact of engineering solutions in a global, economic, environmental, and societal context. | N | |
9) | An ability to communicate verbally and in writing in English at least at the level of B2 of CEFR. | N | |
10) | An understanding the social and environmental aspects of IT applications. | N |
Prepared by and Date | TUNA ÇAKAR , |
Course Coordinator | İLKER BEKMEZCİ |
Semester | Summer School |
Name of Instructor | Asst. Prof. Dr. TUNA ÇAKAR |
Week | Subject |
1) | User Experience in IT - I |
2) | User Experience in IT - II |
3) | Big Data Analytics in Banking - I |
4) | Big Data Analytics in Banking - II |
5) | E-Commerce Applications- I |
6) | E-Commerce Applications - II |
7) | Virtual Reality Applications - I |
8) | Virtual Reality Applications - II |
9) | Augmented Reality with Applications - I |
10) | Augmented Reality with Applications - II |
11) | ITC in Medicine - I |
12) | ITC in Medicine - II |
13) | Brain Technologies and ITC - I |
14) | Brain Technologies and ITC - II |
15) | Final Examination Period |
16) | Final Examination Period |
Required/Recommended Readings | https://developers.google.com/machine-learning/crash-course/first-steps-with-tensorflow/toolkit | ||||||||||||||||||
Teaching Methods | Flipped classroom/Exercise/Laboratory/Active learning | ||||||||||||||||||
Homework and Projects | - | ||||||||||||||||||
Laboratory Work | Each week there will be a lab session | ||||||||||||||||||
Computer Use | Students will apply the methods they learned | ||||||||||||||||||
Other Activities | - | ||||||||||||||||||
Assessment Methods |
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Course Administration |
cakart@mef.edu.tr 02123953600 Course Instructor: Asst. Prof. Tuna Çakar office: A-552 (A block, 5th floor) office hours via appointment by e-mail Grading and evaluation: Evaluation will be based on the student learning outcomes. Missing final exam: Graduate Scgool regulations. Academic integrity: All students of MEF University are expected to be honest and comply with academic integrity. Students are expected to do their own work and neither give nor receive unauthorized assistance. Academic dishonesty and plagiarism will be subject to Law on Higher Education Article 54. You MUST attend the lab sessions to be able to submit your lab work. |
Activity | No/Weeks | Hours | Calculation | ||||
No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
Course Hours | 14 | 2 | 1.5 | 49 | |||
Laboratory | 14 | 2 | 1.5 | 49 | |||
Project | 9 | 2 | 1 | 27 | |||
Midterm(s) | 1 | 30 | 30 | ||||
Final Examination | 1 | 30 | 3 | 33 | |||
Total Workload | 188 | ||||||
Total Workload/25 | 7.5 | ||||||
ECTS | 7.5 |