Courses

About 80% of data science tasks are composed of managing data, from understanding and altering features of the dataset and variables, to combining various datasets. This course introduces the critical tasks of data collection and data wrangling, presentation and understanding of descriptive statistics and basics of...
Instructor: Gabor Bekes
Credits: 1.0
Uncovering patterns in the data can be an important goal in itself, and it is the prerequisite to establishing cause and effect and carrying out predictions. The course starts with simple regression analysis, the method that compares expected y for different values of x to learn the patterns of association between the...
Instructor: Gábor Békés
Credits: 1.0
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: coreScalable 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 systems, and take a look at the architecture...
Instructor: Zoltán Tóth
Credits: 2.0
Type: coreIn this course, you will learn what components make up a data architecture in production and which database technologies are required for different use-cases. We will cover different database technologies and see how they can be used for solving a variety of problems. Then we will take a look at these cloud...
Instructor: Zoltan Toth
Credits: 2.0
Type: core Timing: Full time: Monday, Part-time: SundayIn this course, you will learn what components make up a data architecture in production and which database technologies are required for different use-cases. We will cover different database technologies and see how they can be used for solving a variety of...
Instructor: Zoltán Tóth
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: Zoltán Papp
Credits: 1.0
This 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, neural networks, support vector machine, deep learning etc.). A...
Instructor: Zoltán Papp, Jenő Pál
Credits: 2.0
core for MSc in Technology Management and Innovationelective for MSc in Business AnalyticsThis course focuses on how ITC as a function relates to the overall strategy of firms. It highlights the strategic centricity of ITC as both a core component in the formulation of business strategy but also in the execution of...
Instructor: Yusaf Akbar
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 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