Courses – Fakultet tehničkih nauka u Novom Sadu

Subject: High Performance Computing in Data Science (17.RVP07)

Type of studies	Title
Master Academic Studies	Information Engineering (Year: 1, Semester: Summer)
Master Academic Studies	Information and Analytics Engineering (Year: 1, Semester: Summer)
Master Academic Studies	Computing and Control Engineering (Year: 1, Semester: Summer)

General information:

Category	Scientific-professional
Scientific or art field	Applied Computer Science and Informatics
ECTS	6

Introducing students to the possibillities and techniques of practical application of achitectures, algorithms, and methods of high performance computing in data science.

Students acquire advanced knowledge about applications of high performance computing in data science. Acquired knowledge is used in practice.

Fundamental concepts in data analytics. Implementation and application of selected techniques for data analysis (classification – nearest neighbors, decision trees, support vector machine; clustering – k-means, hierarchical) in HPC systems. Application of HPC in Big Data. Design patterns in HPC and Big Data. Application of Hadoop and Elasticsearch in data analytics. Selected use cases – business analytics, prediction of trends and behaviors, analysis of Web data.

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
White, T.	Hadoop: The Definitive Guide, 4th edition	2015	O’Reilly Media	English
Gheorge, R., Hinman, M. L., Russo, R.	Elasticsearch in Action	2015	Manning Publications	English
Provost, F., Fawcett, T.	Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking	2013	O’Reilly Media, Sebastopol	English
Witten, I. H., Frank, E., Hall, M. A.	Data Mining: Practical Machine Learning Tools and Techniques, 3rd edition	2011	Morgan Kaufmann	English