Courses

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Instructor: *
Credits: 2.0
*Banks today are primarily IT companies, at least from an operational perspective. Many of the leading European banks has been developing their IT infrastructure/applications over decades and most of them struggle with the underlying complexity and cost. Increasing demand from customers for digitization, novel...
Instructor: Szabolcs Szalay
Credits: 2.0
Type: core for MSc in Business Analytics ( Full...
Instructor: Marc Kaufmann
Credits: 2.0
IBM SPSS Modeler is an extensive predictive analytics platform with an intuitive graphical interface. It provides a wide range of advanced statistical and data mining algorithms, which allows users to perform complex data analysis and to extract business value from data.This introductory course aims to give an...
Instructor: Gyorgy Kormendi
Credits: 1.0
This course is designed to help the students understand the important concepts and techniques used in Tableau to move from simple to complex visualizations and learn how to combine them in interactive dashboards.
Instructor: Ivett Kovács
Credits: 1.0
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
Core for: MSc in Business Analytics ( Part Time...
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: electiveTiming: Full time: weekday Data analysis in business and policy applications is often aimed at prediction. The course introduces tools to evaluate predictions, such as loss functions or the Brier score. It emphasizes the importance of out-of-sample prediction, the role of stationarity, the dangers of...
Instructor: Gábor Békés
Credits: 2.0
Type: elective for PhD in Business Administration, MA in Economic Policy in Global Markets, MSc in Business Analytics (full-time), MSc in Finance (full-time), MSc in Finance (part-time)Timing: Full time: weekday Decisions in business and policy are often centered on specific interventions, such as changing monetary...
Instructor: Gábor Békés
Credits: 2.0
Instructor: Anikó Hannák (hannaka@ceu.edu, office hours: Tuesdays 4:00pm-5:30pm by appointment)Credits: 2 (4 ECTS)Term: Winter 2017-2018This course will provide a comprehensive introduction to programming with Python, starting from the basics. Beyond confidently using Python, the class will focus on solving problems...
Instructor: Ancsa Hannak
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
Type: electiveTiming: Full time, part time: weekday evening This course will enable students select the right visualization form to their data and present them in a way to engage their audience. We will learn through exercise how data visualizations work, what are the best practices and how to avoid common pitfalls....
Instructor: Krisztina Szűcs
Credits: 1.0
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Instructor: Davide Torsello
Credits: 2.0
The course provides an introduction to the art and science of trading. Various timeframes, markets, instruments and analytical methods will be discussed. Success factors of automated and semi-automated trading strategies will be explored. Students will, in groups, design, backtest and forward-test their own trading...
Instructor: Ferenc Meszaros
Credits: 2.0
IMPORTANT: This course can accommodate a maximum of 30 students. Priority is given to Mathematics students (Master and PhD) and Network Science PhD students. All other students are selected based on the entry test score. Students that take the course for grade have priority over auditors. All students, both registered...
Instructor: Roberta Sinatra
Credits: 3.0
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