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Information
| Code | IEM756 |
| Name | Data Mining Methods II |
| Term | 2023-2024 Academic Year |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SÜLEYMAN BİLGİN KILIÇ |
Course Goal / Objective
Data mining course aims to produce useful information by means of discovering the patterns, basic relationships, interactions, changes, irregularities, rules, and statistically significant structures in the data
Course Content
The course covers the concept of data mining and design of the database, data warehousing and other storage techniques, database or data warehouse server, database objects creation and expansion, creation of database tables, designing and connecting database, creation and designing of the forms and sub forms, creation and designing of database queries, creation of reports, designing and summarizing the data, data cleaning, removing the noisy and inconsistent data, pattern evaluation and identification, data mining (application of intelligent methods to capture data patterns), presentation of information (to perform presentation of information to the users), convert HTML and ASP files to database objects, using and sharing the database on the internet, creation and using data access pages and query design in the data access pages, ensuring the security of the database
Course Precondition
No prerequisites
Resources
Relevant corporate Internet resources
Notes
Related computer packages
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | explain the concepts of econometrics |
| LO02 | construct the economic models |
| LO03 | collect, arrange and analyze the data |
| LO04 | students can use an econometric software |
| LO05 | students define informaiton about statistics, operations research and mathematics |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explains contemporary concepts about Econometrics, Statistics, and Operation Research | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Explains relationships between acquired knowledge about Econometrics, Statistics, and Operation Research | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explains how to apply acquired knowledge in the field to Economics, Business, and other social sciences | 3 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 4 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 1 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research | 3 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | 2 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Searches for new approaches and methods to solve problems being faced | 4 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Collects/analyzes data in a purposeful way | 3 |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | 4 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops solutions for organizations using Econometrics, Statistics, and Operation Research | 3 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research | 4 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | 1 |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study | 2 |
| PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | 2 |
| PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form | |
| PLO19 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on economic and social events by following current issues | |
| PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Remembering basic data mining methods and statistical concepts | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 2 | Discovering the basic interactions and relationships between the variables and dimensionality reduction methods; principal components factor analysis | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 3 | Principal components factor analysis; continued | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 4 | Nonparametric methods: Artificial neural networks method, | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 5 | Artificial neural networks method; continued | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 6 | Parametric methods:Logit analysis | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 7 | Logit analysis; continued | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | Reading relevant parts in the source books according to the weekly program | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Discriminant analysis | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 10 | Discriminant analysis; continued | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 11 | Hierarchical cluster analysis | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 12 | Hierarchical cluster analysis; contiued | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 13 | k-nearest neighbor algorithm | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 14 | Decision tree classification algorithm | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 15 | c4.5 algorithm | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım |
| 16 | Term Exams | Reading relevant parts in the source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 17 | Term Exams | Reading relevant parts in the source books according to the weekly program | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||