Objectives The winter school will bring students together from different technical majors to work jointly on a business development process, where they learn to: Apply practical tools and templates to extend their entrepreneurial skills Analyse a business case and propose a domain plan and business plan Raise self-awareness by reflecting on their motivations, ambitions and Read More …
General learning goals Use basic statistical concepts and techniques and perform appropriate statistical tests Choose and apply suitable visualization techniques Analyze and model data using linear regression, clustering, decision tree mining and association rules learning Read and make simple database schemes and simple queries to a database. Clean data, choose and apply data transformations, data Read More …
Objectives In this meeting the student gets insight into the study program.
Objectives In this meeting the student gets insight into the study program.
Objectives Non Bachelor Data Science wanting to register for this course should reach out to program management via mcs.academic.advisor.bds@tue.nl for formal approval After taking the course, students are able to independently apply and follow established data science research methods for a given problem and data set access, process, and reason about a large, complex dataset given Read More …
Objectives In this meeting the student gets insight into the study program.
Objectives The main learning objective of FPM is to be able to understand the relation between sequential multi-variate event data and processes and, ultimately, to learn how to properly apply data science methods in the context of processes. Specifically, the following learning objectives are intended: to be able to identify challenges and requirements for using Read More …
Objectives This seminar combines teaching research methods (in preparation for a Master project) with providing students with recent and ongoing research in the area of event data analysis and process analysis. We study recent research articles, book chapters, and Master theses on topics along the entire analysis life-cycle. Through presentation and group discussions, we work Read More …
Objectives After taking this course students should be able to: have a detailed understanding of the entire process mining spectrum and the methodology for process mining analysis can derive and pre-process event logs from raw data and have understand and can work with a specialized form of event data such as event knowledge graphs, or Read More …
The Study & Career Orientation Program is intended to support the students in a structured way in their decision-making process towards graduation with a research group of their preference and to prepare students for making choices regarding their future career. The program is mandatory for all students in the DSAI, CSE, IST and ES programs Read More …
Objectives At the end of the Preparation Phase the student is able to (context [C], research question [Q] and project preparation [P]): [C1] summarize and discuss the problem context, domain-knowledge, and the requirements these set [C2] demonstrate an understanding of and discuss the relevant state-of-the-art in research and other prior work in academia (and the organization). [Q1] formulate one or more research questions relevant with respect to the given context and state-of-the-art Read More …
Objectives Non Bachelor Data Science wanting to register for this course should reach out to program management via mcs.academic.advisor.bds@tue.nl for formal approval After taking this course students should be able to independently: recognize the phases of data analytics research and divide the research process in these phases familiarize themselves with techniques to understand a complex dataset Read More …
Objectives After taking this course students should: have a good understanding of process mining, understand the role of data science in today’s society, be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification, be able to apply basic process discovery techniques to learn Read More …
Objectives Acquire state-of-the-art scientific knowledge of a particular topic in the information systems domain. Typical topics are process modeling, workflow management, process mining, web services, service oriented architectures, language transformations, etc. Content People interested in the ‘process side’ of information systems can take the course ‘Capita selecta architecture of information systems’. This course will be Read More …
