Have you ever analyzed some event data and wondered if the steps you take impact the results you get?Or whether the result you obtain match what you expected to find? These are common challenges faced by process mining analysts, who analyze large sets of event data to gain insights into how business processes are executed. Read More …
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 …
Description Reliable analysis of performance problems and their Root Causes (RCs) requires understanding if a case was delayed by other cases in employees’ or teams’ queues of the same process and/or by cases of other processes. The former is described by the multiple execution single object process dimension, and the latter by the single execution Read More …
Company Description TMNL (Transaction Monitoring Netherlands) was established by the five largest Dutch banks; and is the 1st initiative in the world fighting financial crime in a multi-bank setting. TMNL combines transaction data from the various banks and makes meaningful connections between this data. TMNL is creating smart models to detect these potentially unusual transactions Read More …
Learning goals Working with data data exploration statistical techniques data visualisation data mining data organization and data retrieval Programming (customizable, reproducible) Communication skills (visualisations, a poster and a pitch in the assignments) Systematic way to approach problems (“scientific method”)
Background Customer journey thinking is getting more and more established in companies. Customers are getting more volatile with higher expectations and competition is fierce. With customer journey analytics it is possible to use a personal approach on a large dataset of customer behaviour and customer experience. In the field of customer journey analytics multiple well-known Read More …
You’ve learned about process mining during your courses, but how much do you know about creating the event log for process mining? In business, creating the event log required for process mining is one of the most time-intensive, most complex parts of a process mining project. At Konekti, we’ve built a platform that simplifies and Read More …
Process models are used to describe and reason about the execution of a process (e.g., package delivery) where a process instance (package), also called as a case, moves through the system. A case in a process is often subject to interaction with other cases and/or resources (e.g. deliverer), impacting the workflow. Event logs record which Read More …
Philips Healthcare produces an image-guided therapy system, called Azurion, that helps surgeons to execute complex procedures. In the past Master projects at Philips Healthcare, Master students have already developed a visual logfile analysis tool that has been making waves within our organization and conformance checking methods to address anti-patterns describing unwanted behavior. Now, we’re looking Read More …
The course starts with an overview of the BPM domain using a set of twenty BPM use cases. These cover four key BPM activities: model (creating a process model to be used for analysis or enactment), enact (using a process model to control and support concrete cases), analyze (analyzing a process using a process model Read More …
The Winter School usually takes place in a weekend at the start of Q3. Details are announced 1 or 2 months in advance. General course information Students are invited to join the Winter School by the EIT Digital co-location centre in the Netherlands.
This seminar prepares students for their Master project. By studying recent literature, we discuss and identify how to develop a research question, select the right research method, and plan and conduct the right evaluation. In addition, students get in touch with recent and ongoing research and practical application in the area of Processes and Information Read More …
Only for BDMA students
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based Read More …
In this meeting the student gets insight into the study program.
In this meeting the student gets insight into the study program.
Learning goals Students gain insight in basic techniques for processing large amounts of data in an efficient, reliable, and consistent way. Students develop skills in understanding, interpreting, and documenting data and information in the context of realistic scenarios. Students get understanding of the data life cycle and develop skills for structuring their solutions of practical Read More …
The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining the technical skills acquired earlier in the Data Science program with insights gained in methodological courses. Data Challenge 3 is the final course in this series and shall familiarize students with the skills of designing and Read More …
In this DBL, students get a chance to get a first glimpse on process mining. Through a practical case, students will learn the basics of data mining in the context of (business) processes and they build a prediction model for process aspects. In the basic course Data Analytics for Engineers, students have seen the basics Read More …
The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining the technical skills acquired earlier in the Data Science program with insights gained in methodological courses.
This course can only be followed by permission of the responsible lecturer. People interested in the ‘process side’ of information systems can take the course ‘Capita selecta architecture of information systems’. This course will be organized in an ad-hoc manner taking into account the interests of the student. The focus will always be on a Read More …
In this meeting the student gets insight into the BDMA study program.
