NSCPHD1169 Advanced MATLAB for Multivariate Data Analysis

Volume 2013/2014
Education
PhD
Content
The course entitled “Advanced MATLAB” is a 5-day focused at PhD candidate level with an interest in using the programming and analysis software MATLAB (MAtrix LABoratory) for an advanced use of Data Analysis. The course is a perfect follow-up of the course "introductory MATLAB" in which the students and researchers will increase the knowledge about handling and managing their scientific data. The course gives advanced and dedicated lessons of the possibilities of MATLAB.

1-Linear Algebra, 2- Read-import from other sources, 3- Data managing 4- Singular Value Decomposition, 13- Fitting non-linear equations, 14- Reading external hardware, 15- Introduction to Graphical User Interfaces, 16- Exam.
Learning Outcome
Knowledge, skills, competences:
- Linear algebra with MATLAB.
- Data handling: learn different ways of importing, reading and handling data, searching tools and data managing.
- Singular Values decomposition and its application with MATLAB.
- A case study: fitting non-linear equations.
- Iteration of MATLAB with external hardware
- Introduction to Graphical User Interfaces (GUI) with MATLAB
Handouts and scientific papers provided during the course; scripts and source code provided during the course.
- Contact Teaching: the basis of the course teaching will be done by presentations. The students will be able to follow all the exercises in their own computers. - Learning: Apart from the exercises presented at class, the students will be given several exercises that the must solve for the report. - Educational approaches: This course is addressed to PhD student or advanced Master students. The educational background of the students will be different.
  • Category
  • Hours
  • Exam
  • 1
  • Lectures
  • 15
  • Practical exercises
  • 25
  • Project work
  • 25
  • Theory exercises
  • 10
  • Total
  • 76
Credit
3 ECTS
Type of assessment
Written assignment
Written report based on an examination assignment; work out by the participants individually. The reports have to be handed in maximally one week after the last lecture and are evaluated and credited with PASS/FAIL by the course lectures.
Marking scale
passed/not passed
Censorship form
No external censorship