INFORMATION TECHNOLOGIES (MASTER) (WITH THESIS) (ENGLISH) | |||||
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Qualification Awarded | Program Süresi | Toplam Kredi (AKTS) | Öğretim Şekli | Yeterliliğin Düzeyi ve Öğrenme Alanı | |
Master's ( Second Cycle) Degree | 2 | 120 | FULL TIME |
TYÇ, TR-NQF-HE, EQF-LLL, ISCED (2011):Level 7 QF-EHEA:Second Cycle TR-NQF-HE, ISCED (1997-2013): 44,46,48,52,72 |
Course Code: | 3024211551 | ||||||||||
Ders İsmi: | Thesis Study | ||||||||||
Ders Yarıyılı: | Fall | ||||||||||
Ders Kredileri: |
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Language of instruction: | EN | ||||||||||
Ders Koşulu: | |||||||||||
Ders İş Deneyimini Gerektiriyor mu?: | No | ||||||||||
Other Recommended Topics for the Course: | |||||||||||
Type of course: | Necessary | ||||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||||
Course Coordinator : | Assoc. Prof. Esengül SALTÜRK | ||||||||||
Course Lecturer(s): | |||||||||||
Course Assistants: |
Course Objectives: | To carry out the thesis work, which is necessary for the student to receive a master's degree in engineering, under the supervision of the advisor. |
Course Content: | An independent study under the supervision of an advisor: Research on exploring a potential study area. Identification of a specific problem from the selected study area. The results from this research study are written in the thesis document and a possible academic paper, and presented in an oral presentation. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Thesis preperation | Articles on thesis topic |
2) | Thesis preperation | Articles on thesis topic |
3) | Thesis preperation | Articles on thesis topic |
4) | Thesis preperation | Articles on thesis topic |
5) | Thesis preperation | Articles on thesis topic |
6) | Thesis preperation | Articles on thesis topic |
7) | Thesis preperation | Articles on thesis topic |
8) | Thesis preperation | Articles on thesis topic |
9) | Thesis preperation | Articles on thesis topic |
10) | Thesis preperation | Articles on thesis topic |
11) | Thesis preperation | Articles on thesis topic |
12) | Thesis preperation | Articles on thesis topic |
13) | Thesis preperation | Articles on thesis topic |
14) | Thesis preperation | Articles on thesis topic |
15) | Thesis preperation | Articles on thesis topic |
16) | Thesis presentation | Articles on thesis topic |
Course Notes / Textbooks: | Tez konusuyla ilgili makaleler |
References: | Articles on thesis topic |
Ders Öğrenme Kazanımları | 1 |
2 |
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Program Outcomes | |||||||||||
1) Ability to use and apply current technical concepts and practices in the information technologies of software engineering, data management and computer security. | |||||||||||
2) Understanding user needs, analyzing them, and using them in the selection, evaluation, and management of computer-based systems. | |||||||||||
3) Ability to use data structures and develop algorithms. | |||||||||||
4) Ability to analyze and interpret complex big data systems. | |||||||||||
5) Ability to interpret and apply concepts and algorithms in machine learning. | |||||||||||
6) Understanding of the mathematical foundations of deep learning in the field of data analysis and the ability to apply the theory. | |||||||||||
7) Ability to solve complex data structures, develop and apply deep learning models, and interpret artificial intelligence-focused research on these topics. | |||||||||||
8) Ability to apply deep learning techniques and interpret real-world datasets and projects to solve problems in image analysis, natural language processing, and recommendation systems. | |||||||||||
9) Ability to transfer the basic principles and mathematical infrastructure of digital signal processing to practical applications. | |||||||||||
10) Gaining knowledge about the tools and technologies used via the Internet and the different technologies used for server coding languages and tools. | |||||||||||
11) Ability to understand of how genes function in multicellular species, the flow of genetic information in single-cell organisms, and the ability to interpret and apply biotechnology applications. | |||||||||||
12) Being aware of ethical values and understanding the need to conduct research and practice within the framework of these values. |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Ability to use and apply current technical concepts and practices in the information technologies of software engineering, data management and computer security. | 5 |
2) | Understanding user needs, analyzing them, and using them in the selection, evaluation, and management of computer-based systems. | 5 |
3) | Ability to use data structures and develop algorithms. | 5 |
4) | Ability to analyze and interpret complex big data systems. | 5 |
5) | Ability to interpret and apply concepts and algorithms in machine learning. | 5 |
6) | Understanding of the mathematical foundations of deep learning in the field of data analysis and the ability to apply the theory. | 5 |
7) | Ability to solve complex data structures, develop and apply deep learning models, and interpret artificial intelligence-focused research on these topics. | 5 |
8) | Ability to apply deep learning techniques and interpret real-world datasets and projects to solve problems in image analysis, natural language processing, and recommendation systems. | 5 |
9) | Ability to transfer the basic principles and mathematical infrastructure of digital signal processing to practical applications. | 4 |
10) | Gaining knowledge about the tools and technologies used via the Internet and the different technologies used for server coding languages and tools. | 5 |
11) | Ability to understand of how genes function in multicellular species, the flow of genetic information in single-cell organisms, and the ability to interpret and apply biotechnology applications. | 5 |
12) | Being aware of ethical values and understanding the need to conduct research and practice within the framework of these values. | 5 |
Course | |
Okuma | |
Homework |
Sözlü sınav | |
Sunum | |
Tez Sunma |
Semester Requirements | Number of Activities | Level of Contribution |
Semester Final Exam | 1 | % 100 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 0 | |
PERCENTAGE OF FINAL WORK | % 100 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Study Hours Out of Class | 1 | 900 | 900 |
Total Workload | 900 |