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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. Open Education Faculty
  2. Computer Programming
  3. Course Structure Diagram with Credits
  4. Algorithms
  5. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
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Last Updated: 22/10/2025

Code - Course Title Compulsory/Elective Laboratory + Practice ECTS
BİL204U - Algorithms IV. SEMESTER 0 +0 5.0
Language of Instruction Türkçe
Course Type Required Courses
Course Instructor(s) Instructor Çiğdem ÖZBEK
Mode of Delivery Distance Learning
Place of Delivery
Used Educational Platforms
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended YBS406UNEW TRENDS IN PROGRAMMING
Recommended Resources BIL204UALGORITHMS; Internet resources such as books, live lessons, questions, etc. on eKampus (ecampus.anadolu.edu.tr)
Work Placement No internship or practice.
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Algorithm Concept: Algorithm Definition, Algorithm Criteria, Criteria Determining Algorithm Efficiency; Algorithm Types: Purposes of Algorithm Types.
Week - 2 Data Structure: The Concept of Data Structure, Classification of Data Structures; Simple Data Types: Properties of Simple Data Types; Complex Data Structures: Properties of Complex Data Structures.
Week - 3 Computer Programs and Algorithms: The Relationship Between Program Design Process and Algorithm; Algorithm Design: Everyday Language, Pseudocode, Flow Chart, Converting Algorithm Expression to Other Formats.
Week - 4 Decision Structures: Purpose of Decision Structures, If (if) Structure, If-else Structure, Switch Structure; Loops: Loop Usage Purpose, for Structure, while Structure, do-while Structure, Skipping Loop Step, Loop Termination.
Week - 5 Midterm Exam Question Solution - 1
Week - 6 Midterm Exam Question Solution - 2
Week - 7 Midterm
Week - 8 Algorithm Analysis: The Concept of Algorithm Analysis, Time Complexity, Area Complexity, Algorithm Best, Worst and Average Cases; Asymptotic Notation: The Concept of Asymptotic Notation, Determining the Asymptotic Representation of an Algorithm Given Time Complexity.
Week - 9 Sorting Algorithms: Sorting Algorithms, Sorting Algorithms Runtimes; Search Algorithms: Sequential Search, Binary Search, Search Algorithms Runtimes.
Week - 10 List Structures: Basic Functions of List Structures, Differences Between List Types, List Basic Operations; Tree Structures: Basic Functions and Components of Tree Structures, Differences Between Tree Types, Woodworking.
Week - 11 Machine Learning Algorithms: Ability to Classify, Sample, Explain Machine Learning Evaluation Metrics; Genetic Algorithms: Basic Steps of a Genetic Algorithm, Areas where Genetic Algorithms are Used; Cryptographic Algorithms: Ability to Explain the Concept of a Cryptographic Algorithm, Types and Differences of Cryptographic Algorithms.
Week - 12 Final Exam Question Solution - 1
Week - 13 Final Exam Question Solution - 2
Week - 14 Final Exam

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 30
Final Exam 1 70
Toplam (%) 100

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