|
|
| TBB5173 | Data Structures and Algorithms | 2+2+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of BIOSTATISTICS and MEDICAL INFORMATICS | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 2 hours of lectures and 2 hours of practicals per week | | Lecturer | Doç. Dr. Burçin KURT | | Co-Lecturer | | | Language of instruction | | | Professional practise ( internship ) | None | | | | The aim of the course: | | Introduction to data structures and algorithm complexity. For algorithmic solutions Design and use of data structures. Choosing the right data structure for the problem, Algorithm design using data structures, efficient application development, The analysis of the solution from the perspective of accuracy and efficiency
|
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | To be able to analyze productivity of computer programs
| | | | PO - 2 : | To be able to define and use existing data structures
| | | | PO - 3 : | We can define new data structures for the solution of programming problems.
| | | | PO - 4 : | To be able to realize new data structures in solving programming problems. | | | | 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), PO : Learning Outcome | | |
| Algorithm analysis, linked list, stack, sequence, tree, summarization, priority order, Sorting, chart data structures and graph algorithms.
|
| |
| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Java repetition, classes, methods, top and bottom class concepts, inheritance | | | Week 2 | Series | | | Week 3 | Complexity notations | | | Week 4 | Simple sorting algorithms and complexity | | | Week 5 | Simple sorting algorithms and complexity
| | | Week 6 | Stacks and queues | | | Week 7 | Priority order | | | Week 8 | Linked list
| | | Week 9 | Linked list
| | | Week 10 | Mid term | | | Week 11 | Advanced sorting algorithms and complexity
| | | Week 12 | Trees | | | Week 13 | Summarizing | | | Week 14 | Chart data structures | | | Week 15 | Graph algorithms | | | Week 16 | Examination | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 1 | | | 30 | | In-term studies (second mid-term exam) | 1 | | | 20 | | Homework/Assignment/Term-paper | 1 | | | 10 | | End-of-term exam | 1 | | | 40 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 4 | 14 | 56 | | Sınıf dışı çalışma | 3 | 14 | 42 | | Arasınav | 15 | 1 | 15 | | Uygulama | 10 | 2 | 20 | | Ödev | 5 | 3 | 15 | | Proje | 32 | 1 | 32 | | Dönem sonu sınavı | 30 | 1 | 30 | | Total work load | | | 210 |
|