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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS YBS 4007 DATA MINING COMPULSORY 3 0 0 5

Offered By

Management Information Systems

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR CAN AYDIN

Offered to

Management Information Systems

Course Objective

The purpose of the course is give information to students about basic concepts of data mining,algorithms and applications.

Learning Outcomes of the Course Unit

1   Having knowledge about application field of data mining. 2   Identifying data mining processes. 3   Learning methods that can find out hidden patterns in big databases. 4   Applying classification,clustering and association algorithms.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 1.Big Data Concepts 2 2. Big Data Components 3 3.Big data Applications 4 4. Big data storage with Hadoop 5 5. Big data storage with Hadoop 6 6. Big data querying with Apache Spark 7 7. Big data analysis with Apache Spark 8 8. Big data storage with ElasticSearch 9 9. Big data querying with ElasticSearch 10 10. Big data analysis with ElasticSearch 11 11. Big data storage with MongoDB 12 12. Big data query and analysis with MongoDB 13 13. Big data project development 14 14. Big data project development

Recomended or Required Reading

Main Textbook:Han,J. &Kamber,M.(2011).Data Mining Concept and Techniques.Morgan Kaufmann Publishers. Subsidiary Textbooks: Özkan Y. (2008).Veri Madenciliği Yöntemleri,Papatya Yayıncılık,Istanbul Gürsoy,U.T.Ş. (2011).Uygulamalı Veri Madenciliği Sektörel Analizler.Pegem Akademi,Ankara

Planned Learning Activities and Teaching Methods

Participation in the course, homework and exams aiming at analyzing examples.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

Further Notes About Assessment Methods

Students will undergo two exams, one mid-term and one final.

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Preparation for midterm exam 1 20 20 Preparation for final exam 1 25 25 Preparations before/after weekly lectures 12 3 36 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 119

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 5 5 5 5 5 5 5 LO.2 5 5 5 5 5 5 5 5 5 5 5 LO.3 5 5 5 5 5 5 5 5 5 5 5 LO.4 5 5 5 5 5 5 5 5 5 5 5