Subject: Big Data Architectures (17.RVP04 )
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Master Academic Studies | Computing and Control Engineering (Year: 1, Semester: Winter) |
| Master Academic Studies | Information Engineering (Year: 1, Semester: Winter) |
| Master Academic Studies | Information and Analytics Engineering (Year: 1, Semester: Winter) |
| Master Academic Studies | Artificial Intelligence and Machine Learning (Year: 1, Semester: Winter) |
Understanding of concepts and methods in computer systems for Big Data processing and learning techniques for problem solving in this domain.
Students acquire advanced knowledge about development, architectures, and applications of Big Data systems. Acquired knowledge is used in practice and follow-on courses HPC in Scientific Computing and HPC in Data Science.
Concepts and methods in Big Data processing. Computer systems and algorithms for Big Data processing. Layers in Big Data systems (batch, serving, and speed). Fundamentals of Hadoop. Hadoop components - MapReduce system for data processing, HDFS file system, and YARN cluster resource management system. Effiecient searching through large datasets (Elasticsearch). Fundamentals of Big Data applications in scientific computing and data science.
Teaching is performed through lessons, oral, and computer exercises (in the computer classroom), as well as consultations. Through the teaching process, students are constantly motivated to an intensive discussion, problem oriented reasoning, independent study work, and active participation in the whole lecturing process. The prerequisite to enter final exam is to complete all the pre-exam assignments by earning at least 30 points.
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| 2015 | English | |||
| 2015 | English |
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Test | Yes | Yes | 10.00 |
| Test | Yes | Yes | 10.00 |
| Test | Yes | Yes | 10.00 |
| Complex exercises | Yes | Yes | 30.00 |
| Test | Yes | Yes | 10.00 |
| Theoretical part of the exam | No | Yes | 30.00 |
Assoc. Prof. Slavica Kordić
Associate Professor
Lectures
Assoc. Prof. Vladimir Dimitrieski
Associate Professor
Lectures
Assistant - Master Nikola Todorović
Assistant - Master
Computational classes
Assistant - Master Vladimir Ivković
Assistant - Master
Computational classes
Faculty of Technical Sciences
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Contact:
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© 2024. Faculty of Technical Sciences.