Data analysis and Visualisation

Informatika_pictDue to continuous research and development in the field of supercomputing technology and theoretical methods, it is necessary to educate experts able to operate and effectively exploit the state-of-the-art computational resources in research and computing departments. The students of Computational Sciences field of study with Computational Informatics as their specialization are supposed to become those experts in question.

This study program will follow up and further develop the rudimentary knowledge of computer sciences acquired in the Bachelor Study Program. Within the study program, the emphasis is mainly placed on data analysis and their procession, effective exploitation of HPC architectures, parallel programming, numerical methods, and machine learning.

The graduates of Computational Sciences Master Study Program specialized in Data analysis and Visualisation will acquire complex knowledge and gain experience covering broad areas of HPC, particularly computer architectures, parallel programming and data structures as well as big data procession and their analysis.

Diploma thesis topics

Within the specialization students can choose one of the following diploma thesis topics:

  1. Hadoop Technology and its Use in Data Analysis
  2. Task Parallel Library and OpenMP Comparison
  3. Implementation of Deep Learning Algorithm for Accelerators
  4. Extensive/Wide Log-file Analysis using Sequence Alignment Method
  5. Use of HPC in Transportation Optimization Problem Solving
  6. Use of HPC in Time Series Analysis using Fuzzy Logic
  7. 3D Traffic Visualization (via RODOS Transport System Development Centre)
  8. Virtual Simulator for Science, Research and Development Laboratory
  9. Multiple Kinect and its Use.
  10. Rendering in Blender Cycles using Message Passing Interface (MPI)
  11. Interactive Display of Intermediate Results from OpenFOAM in Blender Cycles
  12. Development of Modules for COVISE/OpenCOVER Applications for Science, Research and Development Laboratory

COMPULSORY FACULTATIVE SUBJECTS

1st year

Biologically Inspired Algorithms

Data Analysis Methods I

Data Analysis Methods II

Probability and Statistics

C/C++ Applications Analysis and Optimization

2nd year

Mathematics for Knowledge Procession

Data Analysis Methods III

Text Data Analysis Methods

Neuron Meshes

Use the opportunity to study a field of study which has no parallel within the Czech Republic. You will learn to program effectively and exploit computational resources to solve demanding practical problems. You will use your acquired knowledge no matter if you have only an ordinary laptop, high-performance work station, or a supercomputer right away.

                   










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