MSc in Business Analytics

Title Instructor Credit
Agile Project Management István Ottó Nagy 2.0
Banking IT and Fintech: Bank to the Future Szabolcs Szalay 2.0
Big Data Computing (full time) Zoltán Tóth 2.0
Big Data Computing (part-time) Zoltán Tóth 2.0
Business Economics Marc Kaufmann 2.0
Business Intelligence in Tableau Ivett Kovács 1.0
Consultative Selling and Negotiations Achilles Georgiu 1.5
Data Analysis 1a: Foundation of Data management in R (full-time) Gergely Daróczi 2.0
Data Analysis 1a: Foundation of Data management in R (part-time) Gergerly Daroczi 2.0
Data Analysis 1b: Foundation of Data management in Stata (full-time) Gábor Békés 2.0
Data Analysis 2: Foundations of Statistics Arieda Muco 2.0
Data Analysis 3: Pattern discovery and regression analysis Gábor Békés 1.5
Data Analysis 3: seminar1: Stata (full-time) tba 0.5
Data Analysis 3: seminar2: R (full-time) tba 0.5
Data Analysis 3: seminar3 : R (part-time) tba 0.5
Data Analysis 4: Prediction Analytics with introduction to Machine Learning Gábor Békés 1.5
Data Analysis 4: seminar2: R tba 0.5
Data Analysis 5: Experiments and causal analysis of interventions Gábor Békés 1.5
Data Analysis 5: seminar2: R tba 0.5
Data Infrastructure in Production (full-time) Zoltán Tóth 2.0
Data Infrastructure in Production (part-time) Zoltan Toth 2.0
Data Science and Machine Learning 1: Concepts Szilard Pafka 2.0
Data Science and Machine Learning 2: Tools Szilard Pafka 2.0
Data Visualization Krisztina Szűcs 1.0
Different Shapes of Data László Salló 2.0
Digital Marketing 1 Tibor Farkas 2.0
Digital Marketing 2 - From mass to segment of one Gabor Bacsa 1.0
Digital Strategy Pál Danyi 2.0
Digital Transformation Achilles Georgiu 2.0
e-Leadership Zoltan Buzady 2.0
Ethical Leaders and Integrity Davide Torsello 2.0
Ethics of Big Data Chrys Margaritidis 2.0
Financial Trading Design and Technology Ferenc Meszaros 1.0
Information Lifecycle Management Tibor Voros 2.0
IoT - Industry 4.0 Tamas Boday 2.0
Organizational Behavior and HR Management tba 2.0
Science of Success Albert - László Barabási 2.0
Security and Data Protection Peter Papp 1.0
Seminar series on applied data science in companies Gábor Békés 1.0
Technology Innovation (Cognitive and Smart Systems) Norbert Sepp 2.0
Tools for Analytics Lab - SPSS Gyorgy Kormendi 1.0

The program requires the fulfillment of 28 credits of course work plus the final project (8 credits). Core courses such as data analysis, big data analytics or data science and machine learning take up 18 credits.

* Please note that elective courses may be subject to change on a demand basis.