Course Structure Diagram with Credits

To see the course details (such as objectives, learning outcomes, content, assessment and ECTS workload), click the relevant Course Code given in the table below.

1. Year Fall Semester
Code Pre. Course Name Theory App/Lab Local Credits ECTS
BEN 501 Research Methods and Design of Experiments 3 0 3 7.5
ELEC 001 Elective Course I 3 0 3 7.5
ELEC 002 Elective Course II 3 0 3 7.5
ELEC 003 Elective Course III 3 0 3 7.5
Total : 30
1. Year Spring Semester
Code Pre. Course Name Theory App/Lab Local Credits ECTS
ELEC 004 Elective Course IV 3 0 3 7.5
ELEC 005 Elective Course V 3 0 3 7.5
ELEC 006 Elective Course VI 3 0 3 7.5
GS 595 Seminar 0 0 0 7.5
Total : 30
2. Year Fall Semester
Code Pre. Course Name Theory App/Lab Local Credits ECTS
GS 599 Master Thesis 0 0 0 30
Total : 30
2. Year Spring Semester
Code Pre. Course Name Theory App/Lab Local Credits ECTS
GS 599 Master Thesis 0 0 0 30
Total : 30
Elective Courses
Code Pre. Course Name Theory App/Lab Local Credits ECTS
BEN 502 Transport Phenomena 3 0 3 7.5
BEN 503 Advanced Molecular Biology 3 0 3 7.5
BEN 504 Advanced Biomedical Engineering 3 0 3 7.5
BEN 505 Advanced Fermentation Technologies 3 0 3 7.5
BEN 506 Biofuels 3 0 3 7.5
BEN 509 Enzyme Kinetics 2 1 3 7.5
BEN 511 Designing with Biomaterials 2 1 3 7.5
BEN 512 Design Methods for Biosystems 3 0 3 7.5
BEN 513 Molecular Basis of Gene Therapy 3 0 3 7.5
BEN 514 Epigenetic Bases of Human Diseases 3 0 3 7.5
BEN 515 Instrumental Analysis of Biomolecules 3 0 3 7.5
BEN 516 Protein Structure, Function and Engineering 3 0 3 7.5
BEN 517 Biomimetics 3 0 3 7.5
BEN 518 Biophysics and Application of Biophysics 3 0 3 7.5
BEN 519 Advanced Bioinformatics 3 0 3 7.5
BEN 520 Functional Oligonucleotides 3 0 3 7.5
BEN 521 Structure, Property and Processing Relations in Polymers 3 0 3 7.5
BEN 522 Advanced Medical Image Analysis 3 0 3 7.5
BEN 523 Synthesis and Characterization of Nanomaterials 3 0 3 7.5
CE 531 Machine Learning 3 0 3 7.5
CE 533 Artificial Intelligence 3 0 3 7.5
CE 536 Human-Computer Interaction 3 0 3 7.5
CE 609 Advanced Numerical Analysis 3 0 3 7.5
EEE 501 Applied Digital Image Processing 3 0 3 7.5
EEE 502 Pattern Recognition 3 0 3 7.5
EEE 505 Biomedical Signals and Instrumentations 3 0 3 7.5
EEE 551 Linear Systems Theory 3 0 3 7.5
MATH 602 Advanced Linear Algebra and Optimization 3 0 3 7.5
Additional Notes

Students are required to have a total of 120 ECTS in order to complete their thesis graduate program.

In order to graduate from Thesis Program, students are required to take 7 courses (1 compulsory + 6 electives), a seminar and a master's thesis.

-Elective Course I (ELEC 001) must be chosen from the following three courses: BEN 502, BEN 503, BEN 504.

-Elective Course II, III, V and VI (ELEC 002, ELEC 003, ELEC 005 and ELEC 006) must be selected from courses other than the aforementioned three courses (BEN 502, BEN 503, BEN 504). There is no restriction for Elective Course IV (ELEC 004).

The Master's program with thesis is mainly prepared for 2 academic years. Program language is English and registered students are required to complete all obligations in this language. There are 3 basic criteria for completion of the Master's program:

- Successful completion of basic, specialized and elective courses to complete at least 21 credits,

- To have a GPA of at least 3.00 out of 4.00 on the basis of the grading system of Izmir University of Economics (Students must take at least CC from the credited courses and the non-credit courses must be S-successful),

- Completion and defense of master's thesis and approval by thesis committee.

 

 

If you need support for these courses due to your disability, please refer to Disability Support Unit. Contact; engelsiz@ieu.edu.tr

Curriculum (Before 2013)