| Course Unit Code | 460-4101/01 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Optional |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | Second Year |
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| Semester when the Course Unit is delivered | Winter Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| PLA06 | prof. Ing. Jan Platoš, Ph.D. |
| Summary |
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Students, during the course, are introduced to the basic approaches, methods and algorithms from big data processing.
The lectures will provide the necessary amount of theory so that it can be applied during the individual work of the students on the tutorials.
Tutorials will provide space for discussing the problems, showing practical tasks and exercising on simple examples. |
| Learning Outcomes of the Course Unit |
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| Evaluation and interpretation of information obtained from the measured and recorded Gig Data from the practice. Methods of data mining, mathematical, statistical and logical methods for solving this class of research and practical problems. |
| Course Contents |
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Modelling in Big data
Behavior Detection
Metric and topological properties
Dimension reduction methods
Log analysis
Visualization of Data
Clustering on Big Data
Machine Learning
NoSQL database
Graph database |
| Recommended or Required Reading |
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| Required Reading: |
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Fatos Xhafa, Leonard Barolli, Admir Barolli, Petraq Papajorgji.Modeling and Processing for Next-Generation Big-Data Technologies: With Applications and Case Studies. Springer 2014.
Robinson, Ian; Webber, Jim; Eifrem, Emil.Graph Databases. O'Reilly Media. 2014.
O'Reilly Radar Team. Big Data Now: Current Perspectives from O'Reilly Radar, O'Reilly Media. 2014.
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Fatos Xhafa, Leonard Barolli, Admir Barolli, Petraq Papajorgji.Modeling and Processing for Next-Generation Big-Data Technologies: With Applications and Case Studies. Springer 2014.
Robinson, Ian; Webber, Jim; Eifrem, Emil.Graph Databases. O'Reilly Media. 2014.
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| Recommended Reading: |
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O'Reilly Radar Team. Big Data Now: Current Perspectives from O'Reilly Radar, O'Reilly Media. 2014.
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O'Reilly Radar Team. Big Data Now: Current Perspectives from O'Reilly Radar, O'Reilly Media. 2014.
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| Planned learning activities and teaching methods |
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| Lectures, Tutorials |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Graded credit | Graded credit | 100 | 51 |