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Use of Matlab in Practice, Numerical Data Analysis

Data

Official data in SubjectManager for the following academic year: 2026-2027

Course director

Number of hours/semester

lectures: 0 hours

practices: 12 hours

seminars: 0 hours

total of: 12 hours

Subject data

  • Code of subject: ÚJ_OAF-MLA-T
  • 1 kredit
  • General Medicine
  • Optional modul
  • spring semester
Prerequisites:

-

Course headcount limitations

min. 5 – max. 20

Available as Campus course for . Campus-karok: ÁOK GYTK TTK

Topic

MATLAB is a widely used software environment that allows us to analyse data and present it in a variety of visual forms with ease. It enables mathematical operations to be performed even on large datasets. Data may originate from very different sources, such as measurements, databases, or spreadsheets. By integrating these data into a common framework, various mathematical and statistical operations can be carried out.

During the course, students will learn how to start developing a MATLAB script, from data import through processing to visualisation. As instructions are compiled using JIT (Just-In-Time) compilation, simple code is easy to read, can be checked at any time, and can be further developed without difficulty.

MATLAB is available free of charge for university students, whether installed on a personal computer, used online, or accessed via mobile platforms. The software provides a wide range of built-in tools for tasks across many scientific fields, such as toolboxes for working with neural networks. By the end of the course, students will reach a level at which they are able to independently analyse and visualise data for thesis projects and TDK work, tailored to the specific requirements of their research. Building on this knowledge, students will be able to learn and apply additional toolboxes independently.

No prior knowledge of MATLAB is required for this course; it starts entirely from the basics.

Lectures

Practices

  • 1.

    Overview of the MATLAB interface, execution options, and debugging. Overview of the Help and documentation tools.

    - Radó János
  • 2.

    Overview and use of available variables. Basic mathematical operations.

    - Radó János
  • 3.

    Overview of plotting (plot, subplot, mesh, surf, etc.)

    - Radó János
  • 4.

    Sorting data (sort, etc.), searching (find, etc.), and indexing.

    - Radó János
  • 5.

    Overview of import and export options

    - Radó János
  • 6.

    Conditional statements in MATLAB

    - Radó János
  • 7.

    Function fitting (fit, cftool, etc.) and defining custom mathematical functions

    - Radó János
  • 8.

    Working with tables

    - Radó János
  • 9.

    Working with images and videos

    - Radó János
  • 10.

    Creating functions (using function)

    - Radó János
  • 11.

    Generating statistics

    - Radó János
  • 12.

    Measuring execution time and publishing options. Task solving, task review, and task submission.

    - Radó János

Seminars

Reading material

Obligatory literature

Literature developed by the Department

The practical materials are available on the MS Teams platform.

Notes

Recommended literature

Teaching materials:
https://matlabacademy.mathworks.com

Practice materials:
https://www.mathworks.com/matlabcentral/cody/

Conditions for acceptance of the semester

-

Mid-term exams

Development of an individual program at the end of the course based on a pre-agreed assignment

Making up for missed classes

By successfully completing the mid-semester test

Exam topics/questions

No exam

Examiners

Instructor / tutor of practices and seminars

  • Radó János
Rólunk