Information Systems Engineering
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

FET308

Ders İsmi:

Data Mining

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Laboratory	ECTS
2	1	0	5

Language of instruction:

Turkish

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Asst. Prof. Dr. SAJJAD NEMATZADEH MİANDOAB

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	This course aims to explain the basic concepts of data mining to students in an applied way.
Course Content:	The course covers data science fundamentals, programming with python, data preparation, descriptive methods and predictive methods.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
1) Defines the basic concepts of data science.
2) Writes programs in languages commonly used in data science (Python, R, etc.).
3) Performs basic operations and processes on data.
4) Analyzes and visualizes data formats and sets.
5) Using predictive methods, distinguishes data that contributes to projects in accordance with their topics.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Fundamentals of Data Mining
2)	Data and Data Science Concepts
3)	Data Discovery
4)	Python Programming
5)	Data Editing with Python
6)	Predictive Methods
7)	Decision Trees
8)	Midterm
9)	Classification and Regression
10)	Machine Learning
11)	Descriptive Methods
12)	Clustering
13)	Association Rules
14)	Project Presentations
15)	Final Exam

Sources

Course Notes / Textbooks:	TAN, Pang-Ning; STEINBACH, Michael, KUMAR, Vipin, Introduction to data mining. Pearson Education India, 2016.
References:	AGGARWAL, Charu C. Data mining: the textbook. Springer, 2015.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4	5
Program Outcomes
1) Adequate knowledge in the fields of mathematics and science; ability to use theoretical and practical knowledge in these fields
2) Adequate knowledge in subjects specific to the relevant engineering discipline; ability to use theoretical and applied knowledge in these areas to solve complex engineering problems.
3) Ability to identify, formulate and solve complex engineering problems.
4) Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.
5) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements.
6) Ability to apply modern design methods to design a complex system, process, device or product.
7) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice.
8) Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.
9) Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.
10) Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.
11) Ability to work effectively in disciplinary teams.
12) Ability to work effectively in multidisciplinary teams.
13) Ability to work individually.
14) Ability to communicate effectively both orally and in writing.
15) Knowledge of at least one foreign language.
16) Effective report writing and comprehension of written reports, ability to prepare design and production reports.
17) Ability to make effective presentations, give and receive clear and understandable instructions.
18) Awareness of the necessity of lifelong learning.
19) Ability to access information, to follow developments in science and technology and to continuously renew oneself.
20) Knowledge about acting in accordance with ethical principles, professional and ethical responsibility and standards used in engineering practices.
21) Knowledge of business practices such as project management, risk management and change management.
22) Awareness about entrepreneurship and innovation.
23) Knowledge about sustainable development.
24) Knowledge about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems of the era reflected in the field of engineering.
25) Awareness of the legal implications of engineering solutions.

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in the fields of mathematics and science; ability to use theoretical and practical knowledge in these fields
2)	Adequate knowledge in subjects specific to the relevant engineering discipline; ability to use theoretical and applied knowledge in these areas to solve complex engineering problems.
3)	Ability to identify, formulate and solve complex engineering problems.
4)	Ability to select and apply appropriate analysis and modeling methods to complex engineering problems.
5)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements.	5
6)	Ability to apply modern design methods to design a complex system, process, device or product.	5
7)	Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice.	5
8)	Ability to use information technologies effectively to analyze and solve complex problems encountered in engineering applications.	4
9)	Ability to design and conduct experiments to investigate complex engineering problems or discipline-specific research topics.	5
10)	Ability to collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics.	4
11)	Ability to work effectively in disciplinary teams.	3
12)	Ability to work effectively in multidisciplinary teams.
13)	Ability to work individually.
14)	Ability to communicate effectively both orally and in writing.
15)	Knowledge of at least one foreign language.
16)	Effective report writing and comprehension of written reports, ability to prepare design and production reports.
17)	Ability to make effective presentations, give and receive clear and understandable instructions.
18)	Awareness of the necessity of lifelong learning.
19)	Ability to access information, to follow developments in science and technology and to continuously renew oneself.
20)	Knowledge about acting in accordance with ethical principles, professional and ethical responsibility and standards used in engineering practices.
21)	Knowledge of business practices such as project management, risk management and change management.
22)	Awareness about entrepreneurship and innovation.
23)	Knowledge about sustainable development.
24)	Knowledge about the effects of engineering applications on health, environment and safety in universal and social dimensions and the problems of the era reflected in the field of engineering.
25)	Awareness of the legal implications of engineering solutions.

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
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PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
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