Course Name Code Semester T+U Hours Credit ECTS
Data Mining BSM 429 7 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Doç.Dr. NİLÜFER YURTAY
Course Lecturers
Course Assistants
Course Category
Course Objective It is aimed to teach data mining technics and thier applications in this course
Course Content Introduction to data minig, their definitions, backrground, operations, algorithms. Data mining applications and problems. Text minig, web mining. Examples.
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Expose relations in data heaps automatically. Lecture, Drilland Practice, Group Study, Project Based Learning, Testing, Homework, Performance Task,
Week Course Topics Preliminary Preparation
1 General definitions.
2 Application areas of data mining
3 Data warehouses and OLAP
4 Data mining models
5 Classification -decision trees
6 Classification statistic algorithms
7 Classification distance algorithms
8 Classification artificial neural networks
9 Association rules and relation analysis
10 Clustering- hierarchical methods
11 Partitioning methods
12 Density based algorithms
13 Grid based algorithms
14 Web mining
Resources
Course Notes [1]Lecture Notes Sakarya Universty
Course Resources [2]Silahtaroğlu,G., Veri Madenciliği, Papatya Yayınevi,2008
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 To have sufficient foundations on engineering subjects such as science and discrete mathematics, probability/statistics; an ability to use theoretical and applied knowledge of these subjects together for engineering solutions, X
2 An ability to determine, describe, formulate and solve engineering problems; for this purpose, an ability to select and apply proper analytic and modeling methods,al background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations X
3 An ability to select and use modern techniques and tools for engineering applications; an ability to use information technologies efficiently, X
4 An ability to analyze a system, a component or a process and design a system under real limits to meet desired needs; in this direction, an ability to apply modern design methods, X
5 An ability to design, conduct experiment, collect data, analyze and comment on the results and consciousness of becoming a volunteer on research, X
6 Understanding, awareness of administration, control, development and security/reliability issues about information technologies, X
7 An ability to work efficiently in multidisciplinary teams, self confidence to take responsibility, X
8 An ability to present himself/herself or a problem with oral/written techniques and have efficient communication skills; know at least one extra language, X
9 An awareness about importance of lifelong learning; an ability to update his/her knowledge continuously by means of following advances in science and technology, X
10 Understanding, practicing of professional and ethical responsibilities, an ability to disseminate this responsibility on society, X
11 An understanding of project management, workplace applications, health issues of laborers, environment and job safety; an awareness about legal consequences of engineering applications, X
12 An understanding universal and local effects of engineering solutions; awareness of entrepreneurial and innovation and to have knowledge about contemporary problems.
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 50
1. Kısa Sınav 10
1. Ödev 30
2. Kısa Sınav 10
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 10 10
Assignment 1 15 15
Final examination 1 10 10
Total Workload 131
Total Workload / 25 (Hours) 5.24
dersAKTSKredisi 5