Spinner

Dokument se učitava

VIŠER

School of Electrical and Computer Engineering of Applied Studies

Belgrade

Big-Data Infrastructure and Services Course code: 317211 | 8 ECTS credits

Basic information
Level of Studies: Master applied studies
Year of Study: 1
Semester: 2
Requirements:
Goal: Enabling students to understand, apply, and develop Big data systems
Outcome: At the end of the course, students will acquire knowledge and skills that will enable them to use modern systems for storing, accessing, analyzing and researchingly structured and unstructured data collections efficiently.
Contents of the course
Theoretical instruction:
  1. The storage, scalability and availability of large amounts of data.
  2. CAP theorem, ACID vs. BASE database features.
  3. Infrastructure of a large amount of data processing system.
  4. Apache Hadoop storage.
  5. Alterative Database Systems (NoSQL).
  6. The features, advantages and disadvantages of the NoSQL database.
  7. Database (bp) key-value type, column-oriented bp, bp oriented with graphs, bp orientated to documents, temporal bp.
  8. Basic Concepts of Data Research. MapReduce and HPCC access to parallel and distributed data processing.
  9. Data flow analysis, data link analysis.
  10. Grouping of Data and Applications in Recommendation Systems.
  11. Analysis of Social Network Graphs.
  12. Dimensional reduction techniques.
  13. Machine learning techniques based on large amounts of data.
Practical instruction (Problem solving sessions/Lab work/Practical training):
  1. Practical lessons follow the theoretical instruction that students are getting to analyze large amounts of data using distributed systems based on Hadoop and HPCC technologies.
Textbooks and References
  1. B.Marr, Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance, Wiley, 2015.
  2. D. Ćulibrk, Otkrivanje znanja iz podataka: Odabrana poglavlja, Create Space, 2012.
  3. M.Minelli, M.Chambers, A.Dhiraj, Big Data, Big Analytics:Emerging Business Intelligence and Analytic Trends for Today’s Businesses, Wiley, 2013.
Number of active classes (weekly)
Lectures: 4
Practical classes: 3
Other types of classes: 0
Grading (maximum number of points: 100)
Pre-exam obligations
Points
activities during lectures
0
activities on practial excersises
10
seminary work
10
colloquium
30
Final exam
Points
Written exam
50
Oral exam
0