Courses

*elective for MSc in Technology Management and InnovationThe course will focus on the use of current reporting and accounting concepts in international business. We will discuss how accounting information can be interpreted and used in managerial decision-making and students will get an overview of financial decision-...
Instructor: Laura Ipacs
Credits: 2.0
The course will focus on the use of current reporting and accounting concepts in international business. We will discuss how accounting information can be interpreted and used in managerial decision-making and students will get an overview of financial decision-making. Financial reporting is a topical issue in current...
Instructor: Laura Ipacs
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: MA in Economic Policy in Global Markets, MSc in Finance (full-time), MSc in Technology Management and Innovation (full-time)Elective for: MA in Global Economic Relations (full-time)The aim of the course is to provide a broad understanding of the principles and techniques of finance, and to apply these to...
Instructor: Peter Szilagyi
Credits: 2.0
core for : MSc in Finance (part-time), MSc in Technology Management and Innovation (part-time), elective for: MA in Global Economic Relations (part-time), The aim of the course is to provide a broad understanding of the principles and techniques of finance, and to apply these to decisions faced by financial managers....
Instructor: Peter Szilagyi
Credits: 2.0
core for MSc In Finance ( Full Time); elective for: MA in Economic Policy in Global Markets, MA in Economics This course offers the financial theory and quantitative tools necessary for understanding how assetprices are determined, and how financial assets are used for investment. The first half of the...
Instructor: Adam Zawadowski
Credits: 4.0
The course takes you through the financial markets, financial instruments, basic analytical tools, strategies. The main objective of the course is to give a structural understanding of the capital markets, products, players to know your way around the financial information jungle which gets deeper every day. The...
Instructor: Tibor Turner
Credits: 4.0
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