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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Vocational School of Information Technologies
  2. Department of Software, Application Development and Analysis
  3. Program in Back-End Software Development
  4. Course Structure Diagram with Credits
  5. Data Structures and Algorithms
  6. Description
  • Description
  • Learning Outcomes
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Last Updated: 01/07/2026

Code - Course Title Course Type Laboratory + Practice ECTS
AYG105 - Data Structures and Algorithms I. SEMESTER 3 +2 6.0
Language of Instruction Türkçe
Course Type Required Courses
Course Instructor(s) ÖĞR. GÖR. DR. NEŞE AGUN
Mode of Delivery Face to face
Place of Delivery
Used Educational Platforms
Prerequisites There are no prerequisites or corequisites for this course.
Courses Recomended
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Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Basic Concepts: Data Types, Algorithm Design, and Pseudocode Fundamentals
Week - 2 Complexity Analysis: Time and Space Complexity, Asymptotic Notations (Big O, Omega, Theta)
Week - 3 Linear Data Structures 1: Arrays and Memory Management in Dynamic Arrays
Week - 4 Linear Data Structures 2: Singly and Doubly Linked Lists
Week - 5 Linear Data Structures 3: Stacks and Queues Applications
Week - 6 Searching and Basic Sorting Algorithms: Linear/Binary Search, Bubble, Insertion, and Selection Sort
Week - 7 Advanced Sorting Algorithms: Quick Sort and Merge Sort
Week - 8 Midterm Exam
Week - 9 Introduction to Hierarchical Data Structures: Tree Concept and Binary Trees
Week - 10 Binary Search Trees (BST) and Balancing Methods (AVL and Red-Black Trees)
Week - 11 Back-End Applications and Database Fundamentals: Hash Tables and Database Indexing Logic
Week - 12 Introduction to Graph Algorithms: Nodes, Edges, and Network Modeling
Week - 13 Advanced Graph Algorithms: Depth-First (DFS) and Breadth-First Search (BFS), Shortest Path Algorithms (Dijkstra)
Week - 14 Advanced Performance Optimization, Algorithmic Problem Solving Applications, and End-of-Term Project Presentations

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