Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Institute of Graduate Programmes
  • Department of Computer Engineering
  • Computer Engineering (Master) (With Thesis) (English)
  • Course Structure Diagram with Credits
  • Advanced Database Management Systems
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load

Course Introduction Information

Code - Course Title BİL546 - Advanced Database Management Systems
Course Type Required Courses
Language of Instruction İngilizce
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOKTOR ÖĞRETİM ÜYESİ BURCU YILMAZEL
Mode of Delivery Formal.
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended None.
Required or Recommended Resources Fundamentals of Database Management Systems" (6th edition), by Ramez Elmasri, and Shamkant B. Navathe
Recommended Reading List Database Systems: The Complete Book, Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom.Database Management Systems, Raghu Ramakrishnan, and Johannes Gehrke.
Assessment methods and criteria Midterm Exam, Homework, and Final.
Work Placement None.
Sustainability Development Goals Quality Education , Industry, Innovation and Infrastructure

Content

Weeks Topics
Week - 1 Introduction to databases and database management systems.
Week - 2 The Entity-Relationship (E/R) model and advanced E/R concepts.
Week - 3 From E/R diagrams to relational schema.
Week - 4 QL basics: Data definition, querying, and data manipulation.
Week - 5 Schema refinement: Functional dependencies, normalization, and normal forms.
Week - 6 Transactions (TXNs): ACID properties and introduction to concurrency control.
Week - 7 NoSQL databases.
Week - 8 Modern data architectures: Data warehouse, data lake, and lakehouse approaches.
Week - 9 Distribution, scalability, and performance approaches in database systems.
Week - 10 Multi-model and specialized database systems.
Week - 11 Geospatial databases in the AI era.
Week - 12 Vector databases and similarity search.
Week - 13 The intersection of AI and databases: AI agents, memory systems, and in-database machine learning.
Week - 14 Data privacy in AI-era databases.

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Problem Solving
  • Report Preparation and/or Presentation
  • Proje Design/Management
  • Competences
  • Questoning
  • Creative
  • Follow ethical and moral rules
  • Problem solving
  • Applying theoretical knowledge into practice
  • Project Design and Management

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 30
Homework 1 20
Final Exam 1 50
Toplam (%) 100
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