Module 1 “Business Data Processing” 11 CP (16.5 ECTS)
Business requirements analysis and specification of information systems (Mini MBA, Mg.bus.man., Mg.inf.sys. J. Paksis, “Emergn”): 2 CP (Part A)
Multivariate data analysis (Dr.oec., prof. B. Sloka): 2 CP (Part A)
Forecasting methods (Dr.sc.comp.h.c., prof. P. Rivža): 2 CP (Part B)
Practical application of Power BI in business data processing (Dr.phys., prof. hon. I. Godmanis): 2 CP (Part A)
Business analytics in SPSS environment (Dr.admin.sc., prof. I. Ludviga): 2 CP (Part A)
Corporate social responsibility and environmental ecology (S. Blumberga): 1 CP (Part A)
Module 2 “Big Data Management” 14 CP (20 ECTS)
Introduction to Big Data and machine learning (Dr.phys., Assoc. I. Godmanis): 3 CP (Part A)
Use of SQL language when working with relational databases (Mg.dat. E. Plācis, “Accenture”: 2 CP (Part A)
R language (Mg.dat. A. Alksnis): 2 CP (Part A)
Data pre-processing and data management using the R language: (Dr.oec., asoc.prof. E. Brēķis): 2 CP (Part B)
Big Data management tools (Mg.eng.sc. A. Vesjolijs, “Accenture”): 3 CP (Part A)
Data visualisation methods (Dr.sc.ing. S. Bērziša): 2 CP (Part B)
Module 3 “Harnessing Big Data in new technologies”: 9 CP (13.5 ECTS)
Python language (Dr.dat., asoc.prof. U. Bojārs): 2 CP (Part B)
Practical machine learning using Python language (Dr.sc.comp. J. Rāts): 2 CP (Part B)
Big data analytics in business – KNIME and other tools (MBA, Chicago uni., U. Sprūdžs): 3 CP (Part B)
Business platforms (Dr.phys, Assoc. I. Godmanis): 2 CP (Part C)
Internship
- 6 CP (with 4-year bachelor’s studies),
- 26 CP (with 3-year bachelor’s studies)
Master’s thesis (20 CP)