Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
INTRODUCTION TO SCIENTIFIC PROGRAMMING SEUE1019 6. Semester 2 + 0 2.0 3.0

Prerequisites None

Language of Instruction English
Course Level Bachelor's Degree
Course Type Elective
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals Main objective is learning definitions, manipulations and operations on matrices and other data types available within Matlab.
Course Content Definition of, manipulation of, and operations on matrices and other data types available within Matlab. Matlab's basic entity, the matrix, multidimensional arrays, cell arrays and structure arrays. Curve fitting on experimental data working with polynomials. Programming in Matlab, scripts and functions in Matlab-code, Working with Matlab function-functions. Numerical integration and optimization on MATLAB functions solving differential equations. Matlab Graphics.
Learning Outcomes 1) Recognize commands and their output in Matlab program.
2) Compute mathematical operations (such as limit, derivative, integral) using computer.
3) Construct simple user defined functions to solve the given problems.
4) Analyze the output of a given program.

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Introduction. Review: matrix operations Lecture
Brainstorming
 Project (Including Preparation and presentation Time) Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
2. Week Matrices and vectors, Matrice and Array Operations Lecture
Brainstorming
 Project (Including Preparation and presentation Time) Report (Including Preparation and presentation Time)
3. Week Interactive Computing Lecture
Brainstorming
 Homework
4. Week Control Structures, Loops, Style Lecture
Brainstorming
 Presentation (Including Preparation Time)
5. Week Switch, Loop , Array Examples Lecture
Brainstorming
 Homework
6. Week Examples, Functions Lecture

 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
7. Week Functions, Recursion Lecture
Brainstorming
 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
8. Week Midterm Question Answer

 Homework
9. Week Matlab Structures and Objects, Strings Lecture
Brainstorming
 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
10. Week File Input Output Lecture
Brainstorming
 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
11. Week Plotting, More on Graphics and Plotting Lecture
Brainstorming
 Homework
12. Week Polynomials, Curve Fitting and Interpolation Lecture
Brainstorming
 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
13. Week Advanced 3-Dimensional Plots Lecture
Brainstorming
 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)
14. Week Applications in Numerical Analysis Lecture
Brainstorming
 Activity (Web Search, Library Work, Trip, Observation, Interview etc.)

Sources Used in This Course
Recommended Sources
Lecturer’s notes

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 2
Work Hour outside Classroom (Preparation, strengthening) 10 3
Midterm Exam 1 6
Time to prepare for Midterm Exam 1 10
Final Exam 1 6
Time to prepare for Final Exam 1 10
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
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Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • ECTS credits and course workload