Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
8BLMS430Problem Solving with R3+0+03510.03.2026

 
Course Details
Language of Instruction Turkish
Level of Course Unit Bachelor's Degree
Department / Program Computer Engineering
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course The aim is to introduce students to R, an open-source programming language. The course focuses on how to perform data analysis using R programming, which has powerful data processing tools, can integrate with relational databases, and can be used in enterprise applications. Students will learn to analyze, visualize, and interpret the concept of big data, which has entered our lives with the digital transformation process, using R programming. This course is intended to provide a foundation for students.
Course Content Introduction to the R Programming Language. Introduction to how to use the R interface and auxiliary tools. Basic data structures in R. Concepts of vectors, factors, matrices, lists, and data frames. The use of character strings in R programming. Data input/output and working with files. Control and loop operations in programs. Drawing various graphics. Statistics with R programming.
Course Methods and Techniques Exam, Project
Prerequisites and co-requisities None
Course Coordinator Asist Prof. Turgut PURA
Name of Lecturers Asist Prof. Turgut PURA
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Özkan, B. & Özkan, Y., (2017), “R ile Programlama”, 1.Baskı, Papatya Bilim Yayınevi.
Course Notes Instructor's Lecture Notes

Course Category
Mathematics and Basic Sciences %90
Field %10

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 40
Assignment 1 % 10
Final examination 1 % 50
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 15 3 45
Hours for off-the-c.r.stud 15 4 60
Assignments 1 4 4
Mid-terms 1 7 7
Final examination 1 15 15
Total Work Load   Number of ECTS Credits 5 131

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Students will learn the R programming language.
2 Students will learn the R programming language.
3 Students will be able to create graphs using R programming.
4 Students will be able to write statistical functions using R programming.
5 Students will be able to work with various data types using R programming.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 R Programlama Diline Giriş
2 Vektör ve Faktörler
3 Dizi ve Matrisler
4 Listeler
5 Veri Çerçevesi
6 Karakter Dizinleri
7 Veri Giriş ve Çıkış İşlemleri
8 Genel Tekrar
9 Program Denetimi
10 Fonksiyonlar
11 Grafikler
12 R ile İstatistik( Merkezi Eğilim Ölçüleri Ve Dağılım Ölçüleri)
13 R ile İstatistik( Olasılık Dağılımları- Normal Dağılım ve Binom Dağılımı)
14 R ile İstatistik( Hipotez Testleri ve Regresyon Analizi)
15 Genel Tekrar

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1 3
C2 3
C3 3
C4 3
C5 3

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  https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=243279&curProgID=5607&lang=en