COMPUTER ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | 1410002013 | ||||||||
Ders İsmi: | Data Mining | ||||||||
Ders Yarıyılı: |
Fall Spring |
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Ders Kredileri: |
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Language of instruction: | TR | ||||||||
Ders Koşulu: | |||||||||
Ders İş Deneyimini Gerektiriyor mu?: | No | ||||||||
Type of course: | Bölüm Seçmeli | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Dr.Öğr.Üyesi Recep DURANAY | ||||||||
Course Lecturer(s): | |||||||||
Course Assistants: |
Course Objectives: | To familiarize the student with the subjects within the scope of data mining. Using classification and clustering algorithms in real life problems, using R software and solving examples related to data mining |
Course Content: | Data: types, quality, preprocessing, proximity, distance measures, summary statistics, imaging, multidimensional data analysis. Classification: decision trees, model evaluation, Bayesian classifiers, neural networks, SVM. Consolidation analysis. Cluster analysis: K-means, HC algorithms, cluster evaluation, other clustering approaches, R software. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | General introduction, data processing, proximity criteria | Lecture Notes |
2) | Summary statistics, viewing, multidimensional data analysis | Lecture Notes |
3) | Introduction of R software | Lecture Notes |
4) | Introduction to classification, decision trees | Lecture Notes |
5) | Model evaluation, Midterm Exam1 | |
6) | Bayesian classifiers, neural networks | Lecture Notes |
7) | SVM, join analysis | Lecture Notes |
8) | Midterm 2 | |
9) | Introduction to cluster analysis, K-means, HC | Lecture Notes |
10) | Fuzzy clustering, SOM | Lecture Notes |
11) | Graph based clustering I | Lecture Notes |
12) | Graph based clustering II | Lecture Notes |
13) | Evaluation of clusters | Lecture Notes |
14) | A case study using R | Lecture Notes |
15) | A case study using R | Lecture Notes |
16) | Final |
Course Notes / Textbooks: | Akademisyen Ders Notu |
References: | Academician Lecture Notes |
Ders Öğrenme Kazanımları | 1 |
2 |
3 |
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Program Outcomes | ||||||||||||||||
1) PO 1.1) Sufficient knowledge in mathematics, science and computer engineering | ||||||||||||||||
2) PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems. | ||||||||||||||||
3) PO 2.1) Identifying complex engineering problems | ||||||||||||||||
4) PO 2.2) Defining complex engineering problems | ||||||||||||||||
5) PO 2.3) Formulating complex engineering problems | ||||||||||||||||
6) PO 2.4) Ability to solve complex engineering problems | ||||||||||||||||
7) PO 2.5) Ability to choose and apply appropriate analysis and modeling methods | ||||||||||||||||
8) PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions. | ||||||||||||||||
9) PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product | ||||||||||||||||
10) PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | ||||||||||||||||
11) PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | ||||||||||||||||
12) PO 4.3) Ability to use information technologies effectively. | ||||||||||||||||
13) PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments | ||||||||||||||||
14) PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation | ||||||||||||||||
15) PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection | ||||||||||||||||
16) PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics | ||||||||||||||||
17) PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | PO 1.1) Sufficient knowledge in mathematics, science and computer engineering | |
2) | PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems. | |
3) | PO 2.1) Identifying complex engineering problems | |
4) | PO 2.2) Defining complex engineering problems | |
5) | PO 2.3) Formulating complex engineering problems | |
6) | PO 2.4) Ability to solve complex engineering problems | |
7) | PO 2.5) Ability to choose and apply appropriate analysis and modeling methods | |
8) | PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions. | |
9) | PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product | |
10) | PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | |
11) | PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications | |
12) | PO 4.3) Ability to use information technologies effectively. | |
13) | PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments | |
14) | PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation | |
15) | PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection | |
16) | PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics | |
17) | PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics |
Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama) | |
Homework |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 10 | % 10 |
Homework Assignments | 2 | % 10 |
Midterms | 2 | % 40 |
Semester Final Exam | 1 | % 40 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Study Hours Out of Class | 30 | 3 | 90 |
Midterms | 2 | 2 | 4 |
Final | 1 | 3 | 3 |
Total Workload | 139 |