Courses

Type: coreTiming: Full time: Monday, Part-time: Sunday Scalable data-analytics workloads introduce new challenges: How can you scale out your data analytics systems if your data size and computational need can’t be satisfied with a single computer?In this course we will cover the basics of distributed Data Analytics...
Instructor: Zoltán Tóth
Credits: 2.0
Type: coreTiming: Full time: Monday, Part-time: Sunday Scalable data-analytics workloads introduce new challenges: How can you scale out your data analytics systems if your data size and computational need can’t be satisfied with a single computer?In this course we will cover the basics of distributed Data Analytics...
Instructor: Zoltán Tóth
Credits: 2.0
Type: core for MSc in Business Analytics ( Full...
Instructor: Marc Kaufmann
Credits: 2.0
Type: core Seminars: Group 1: for full-time students primarily. Group 2: for part-time students in MSc in Business Analytics primarily. Group 3: for MSc in Finance students and all for whom the course in not offered in their program. MA in Economic Policy in Global Markets students have to choose one from Data...
Instructor: Gergely Daroczi
Credits: 2.0
This course is core for: MA in Economic Policy in Global Markets, MSc in Business Analytics, PhD in Business Administrationelective for : MA in Global Economic Relations, MSc in Finance Seminars:Group 1: programming in STATA, full-time schedule, for MA and PhD students primarily. Group 2: programming in R, full-time...
Instructor: Arieda Muço
Credits: 2.0
Type: core for MA in Economic Policy in Global Markets 1st yr, MSc in Business Analytics (full-time), MSc in Business Analytics (part-time)elective for: PhD in Business Administration, MA in Global Economic Relations (full-time), MA in Global Economic Relations (part-time), MSc in Finance (full-time), MSc in Finance (...
Instructor: Gábor Békés
Credits: 2.0
Type: core for MSc in Business analyticsAfter an overview of the entire data science landscape this course will focus on machine learning. The course will introduce the main fundamental concepts in machine learning (supervised learning, training, scoring, accuracy measures, test set, overfitting, cross validation,...
Instructor: Szilard Pafka
Credits: 2.0
Type: core for class of 2017 Sept / elective for class of Mar 2017This course will build on the previous one (which introduced the basic concepts in machine learning) and will discuss state-of-the-art algorithms for supervised learning (linear models, lasso, decision trees, random forests, gradient boosting machines,...
Instructor: Szilard Pafka
Credits: 2.0
core for MSc in Technology Management and Innovationelective for MSc in Business Analytics
Instructor: Zsolt Szeleczki
Credits: 2.0
Type: coreTerm: Winter Timing: Full time, part time: weekday eveningThe past ten years have brought a fundamental change in our lives, and the reason for the changes was technological development itself. In times of crisis and continuously changing environment there is an evidence need for creativity and innovation to...
Instructor: Achilles Georgiu
Credits: 2.0
core for MSc in Technology Management and Innovationelective for MSc in Business Analytics
Instructor: Olaf Zylicz
Credits: 2.0
This seminar series (6x 100 min presentations/talks) will feature prominent practitioners talking about data science projects in their organizations. Talks may cover a variety of topics such as data collection, modelling, production, data warehouse development, data science team building.
Instructor: Gábor Békés
Credits: 1.0
Core for MS in Technology Management and InnovationElective for MS in Business AnalyticsIn recent decades, technology has become one of, if not the primary, most important factors to fuel progress and economic growth. The main driver that enables these positive changes is innovation. Technology innovation is...
Instructor: Norbert Sepp
Credits: 2.0