Information Package / Course Catalogue
Engineering Mathematics
Course Code: ZT114
Course Type: Required
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 3
Objectives of the Course

The aim of this course is to explain linear and non-linear functions, probability density functions and teach optimization, explain derivatives, integrals and the relationship between them, explain matrices and linear models and teach their implementation in the R-Program

Course Content

To teach functions, derivatives, integrals, matrices and matrices-related operations using graphics, optimization, derivative, integral and matrix-related packages in the R-Program

Name of Lecturer(s)
Prof. Kadir KIZILKAYA
Learning Outcomes
1.To understand linear and non-linear functions and their use in agriculture and their application in the computer environment
2.Understand the optimization of functions in a computer environment
3.Understand the use of derivatives and integrals and their application in the computer environment
4.Understand the use of matrices and their application in the computer environment
5.Understand the use of linear models and their application in computer environment
Recommended or Required Reading
1.Kenneth A. Ross, Elementary Analysis: The Theory of Calculus, Springer-Verlag(1980)
2.Çoker ., Özer O., Taş K. ‘’ General Mathematics’’, Volume 1 (1996)
3.Prof.Dr.Mustafa Balcı “General Mathematics I” Balcı Publication
4.R-Program Lecture Notes by Prof. Dr. Kadir KIZILKAYA
Weekly Detailed Course Contents
Week 1 - Theoretical & Practice
Functions and Introduction to R-Program
Week 2 - Theoretical & Practice
Linear and Non-Linear Functions and Applications of R-Programming
Week 3 - Theoretical & Practice
Optimization of Functions and Applications of R-Programming
Week 4 - Theoretical & Practice
Probability Density Functions and Applications of R-Programming
Week 5 - Theoretical & Practice
Derivative and Applications of R-Programming
Week 6 - Theoretical & Practice
Derivative and Applications of R-Programming
Week 7 - Theoretical & Practice
Integral and Applications of R-Programming
Week 8 - Theoretical & Practice
Integral and Applications of R-Programming
Week 9 - Theoretical & Practice
Matrices and Applications of R-Programming
Week 10 - Theoretical & Practice
Determinant of Matrix and Applications of R-Programming
Week 11 - Theoretical & Practice
Inverse of Matrix and Applications of R-Programming
Week 12 - Theoretical & Practice
Matrix Applications and Applications of R-Programming
Week 13 - Theoretical & Practice
Linear Models and Applications of R-Programming
Week 14 - Theoretical & Practice
Linear Models and Applications of R-Programming
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140228
Midterm Examination1516
Final Examination115116
TOTAL WORKLOAD (hours)78
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
2
2
1
OÇ-2
1
1
3
2
OÇ-3
1
1
1
OÇ-4
2
2
3
2
2
OÇ-5
1
1
3
2
2
Adnan Menderes University - Information Package / Course Catalogue
2026