MEDICINE
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
CMP4336	Introduction to Data Mining	Fall	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR
Recommended Optional Program Components:	None
Course Objectives:	In this course, data mining algorithms and computational paradigms that are used to extract useful knowledge, extract patterns and regularities in databases, and perform prediction and forecasting will be discussed. Supervised and unsupervised learning approaches will be covered with a focus on pattern discovery and cluster analysis.

Learning Outcomes

The students who have succeeded in this course;
1. Be able to understand Data Gathering and Pre-processing
2. Become familiar with Frequent Item Set Detection
3. Be able to understand Association Rule Mining
4. Be able to understand Classifiers, and their benefits
5. Be able to use Clustering
6. Be able to understand Clustering Evaluation

Course Content

1.Introduction to Basic Concepts
2.Data Exploration
3.Classification
4.Clustering
5.Dimensionality Reduction
6.Frequent Item Set Mining
7.Association Rule Mining

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Basic Concepts	None
2)	Data Exploration: Summary Statistics, Visualization, OLAP and Multi-dimensional Data Analysis	None
3)	Data Pre-Processing, Transformation, Normalization, Standardization	None
4)	Classification and Regression: Model Selection and Generalization, Decision Trees, Performance Evaluation	None
5)	Classification: Bayesian Decision Theory, Parametric Classification, Naive Bayes Classifier, Instance-Based Classifiers
6)	Classification	None
6)	Classification and Regression: Artificial Neural Networks, Support Vector Machines
7)	Midterm I	Review of all topics covered so far
8)	Clustering: Partitioning and Hierarchical Algorithms	None
9)	Clustering: Density-Based Algorithms
10)	Cluster Evaluation, Comparing Clusterings	None
11)	Midterm II	none
12)	Dimensionality Reduction	none
13)	Frequent Item Set Mining	none
14)	Association Rule Mining	none

Sources

Course Notes / Textbooks:	Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach and Vipin Kumar
References:	Data Mining: Concepts and Techniques, by Jiawei Han, Micheline Kamber and Jian Pei

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 20
Project	1	% 20
Midterms	2	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	42
Study Hours Out of Class	16	32
Project	5	15
Homework Assignments	6	12
Midterms	8	28
Final	6	26
Total Workload		155

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Integrates the knowledge, skills and attitudes acquired from basic and clinical medical sciences, behavioral sciences and social sciences, and uses them in health service delivery.
2)	In patient management, shows a biopsychosocial approach that takes into account the socio-demographic and sociocultural background of the individual, regardless of language, religion, race and gender.
3)	In the provision of health services, prioritizes the protection and development of the health of individuals and society.
4)	Taking into account the individual, societal, social and environmental factors affecting health; does the necessary work to maintain and improve the state of health.
5)	By recognizing the characteristics, needs and expectations of the target audience, provides health education to healthy/sick individuals and their relatives and other healthcare professionals.
6)	Shows a safe, rational and effective approach in health service delivery, prevention, diagnosis, treatment, follow-up and rehabilitation processes.
7)	Performs invasive and/or non-invasive procedures in diagnosis, treatment, follow-up and rehabilitation processes in a safe and effective way for the patient.
8)	Provides health services by considering patient and employee health and safety.
9)	In the provision of health services, takes into account the changes in the physical and socioeconomic environment on a regional and global scale, as well as the changes in the individual characteristics and behaviors of the people who apply to it.
10)	Takes good medical practice into account while carrying out his/her profession.
11)	Fulfills its duties and obligations within the framework of ethical principles, rights and legal responsibilities required by its profession.
12)	Demonstrates decisive behavior in providing high-quality health care, taking into account the integrity of the patient.
13)	Evaluates his/her performance in his/her professional practice by considering his/her emotions and cognitive characteristics.
14)	Advocates improving the provision of health services by considering the concepts of social reliability and social responsibility for the protection and development of public health.
15)	Can plan and carry out service delivery, training and consultancy processes related to individual and community health in cooperation with all components for the protection and development of health.
16)	Evaluates the impact of health policies and practices on individual and community health indicators and advocates increasing the quality of health services.
17)	The physician attaches importance to the protection of his/her own physical, mental and social health, and does what is necessary for this
18)	Shows exemplary behavior and leads the healthcare team during service delivery.
19)	Uses resources cost-effectively, for the benefit of society and in accordance with the legislation, in the planning, implementation and evaluation processes of health services in the health institution he/she is the manager of.
20)	Establishes positive communication within the health team it serves and assumes different team roles when necessary.
21)	Is aware of the duties and responsibilities of the health workers in the health team and acts accordingly.
22)	In the professional practices, works in harmony and effectively with the colleagues and other professional groups.
23)	Communicates effectively with patients, their relatives, healthcare professionals, other professional groups, institutions and organizations.
24)	Communicates effectively with individuals and groups that require a special approach and have different socio-cultural characteristics.
25)	In the diagnosis, treatment, follow-up and rehabilitation processes, shows a patient-centered approach that associates the patient with the decision-making mechanisms.
26)	Plans and implements scientific research, when necessary, for the population it serves, and uses the results and/or the results of other research for the benefit of the society.
27)	Reaches and critically evaluates current literature knowledge about his/her profession.
28)	Applies the principles of evidence-based medicine in clinical decision making.
29)	Uses information technologies to increase the effectiveness of its work on health care, research and education.
30)	Effectively manages individual work processes and career development.
31)	Demonstrates skills in acquiring and evaluating new knowledge, integrating it with existing knowledge, applying it to professional situations and adapting to changing conditions throughout professional life.
32)	Selects the right learning resources to improve the quality of the health service it offers, organizes its own learning process