TÜRKÇE
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Information
| Unit | FACULTY OF ENGINEERING |
| INDUSTRIAL ENGINEERING PR. | |
| Code | ENM352 |
| Name | Database Management and Data Mining |
| Term | 2018-2019 Academic Year |
| Semester | 6. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Öğr. Gör. Dr. İRFAN MACİT |
| Course Instructor |
Öğr. Gör. Dr. İRFAN MACİT
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of the course is to design, develop and program a database system and to facilitate the basic concepts of
Course Content
Introduction to Database Management System, Database Design, Data Normalisation, Data Queries, Advanced Data Queries and Introduction to Data Mining and its Applications
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Finding solutions to real life problems |
| LO02 | Being able to design a Database Management System |
| LO03 | Being able to use any of A Database Management System |
| LO04 | Implementing SQL Query Language |
| LO05 | Being able to use data mining techniques |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has sufficient background on topics related to mathematics, physical sciences and industrial engineering. | 4 |
| PLO02 | - | Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods. | 5 |
| PLO03 | - | Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems . | 4 |
| PLO04 | - | Gains ability to choose and apply methods and tools for industrial engineering applications. | 4 |
| PLO05 | - | Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions. | 5 |
| PLO06 | - | Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team. | 4 |
| PLO07 | - | Can access information and to search/use databases and other sources for information gathering. | 5 |
| PLO08 | - | Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously. | 5 |
| PLO09 | - | Can use computer software in industrial engineering along with information and communication technologies. | 5 |
| PLO10 | - | Can use oral and written communication efficiently. | 3 |
| PLO11 | - | Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession. | 3 |
| PLO12 | - | Has a conscious understanding of professional and ethical responsibilities. | 3 |
| PLO13 | - | Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice. | 2 |
| PLO14 | - | Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Database Management Introduction | Reading of related sources and lecture notes | |
| 2 | Database Design | Reading of related sources and lecture notes | |
| 3 | Data Normalization | Reading of related sources and lecture notes | |
| 4 | Data Queries | Reading of related sources and lecture notes | |
| 5 | Advanced Queries and Subqueries | Reading of related sources and lecture notes | |
| 6 | Forms | Reading of related sources and lecture notes | |
| 7 | Reports | Reading of related sources and lecture notes | |
| 8 | Midterm exam | Study for Exam | |
| 9 | Calculations and Data Manupilation | Reading of related sources and lecture notes | |
| 10 | Application Development | Reading of related sources and lecture notes | |
| 11 | Access Software SQL Develepment | Reading of related sources and lecture notes | |
| 12 | Data mining Introduction | Reading of related sources and lecture notes | |
| 13 | Data mining Applications | Reading of related sources and lecture notes | |
| 14 | WEKA Data mining Software Introduction | Reading of related sources and lecture notes | |
| 15 | WEKA data mining applications | Reading of related sources and lecture notes | |
| 16 | Final exam | Study for Exam | |
| 17 | Final exam | Study for Exam |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
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 | 2 | 28 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 6 | 6 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 6 | 6 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 100 | ||
| Total Workload / 25 (h) | 4,00 | ||
| ECTS | 4 ECTS | ||