Top 5 presentations of DIS2015 (Data Science Innovation Summit).

Dear friends,

March 26th will be the milestone of our community.

We had 68 speakers at our Data Innovation Summit with over 500 attendants. Check our new DataScience video channel with all the presentations. Pictures of the event are available on our facebook page. Over 600 people replied to the datascience survey.  Read Ward’s analysis of the satisfaction survey.

Here is the top 5 of the presentations:

  • Kris Peeters: The people aspect of Data Science (view)
  • Elena Tsiporkova: Data Innovation Lab (view)
  • Toon Vanagt: How Open Data allows faster innovation (view)
  • Hans Constandt: The disruptive Role of startups in Data Innovation (view)
  • Steven Beeckman: Government and Data (view)

Thank you for participating to the Data Science Survey. The results are still available to all participants. Here is a summary done by our experts:

  • Data Innovation Summit Dashboard by Dieter and Nicholas (view)
  • Data Innovation Survey results – In Neo4j by Rik (view)
  • The question “Are all Data Scientists nerds?” – By Nele (view)
  • Data Innovation Survey 2015 – preliminary analysis by Ward (view)

The plan is to bundle these in a e-book, if you want to be part of this book you only need to submit your analysis. We are still waiting for a team that wants to link this survey with another existing survey. Winners of the best analysis will be announced during our Banking meetup on May 20th.

Thank you for all for making this summit a success.

Philippe Van Impe

Join us on our next meetup:

Brussels Data Science Meetup

Brussels, BE
1,161 Business & Data Science pro’s

The Brussels Data Science Community:Mission:  Our mission is to educate, inspire and empower scholars and professionals to apply data sciences to address humanity’s grand cha…

Next Meetup

Data for Good & Kaggle competitions

Thursday, Apr 23, 2015, 6:30 PM
86 Attending

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New Links:

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Free webinar on Analytics in a Big Data World by Bart Baesens.

Baesens_Bart_small

Nice overview on how analytics and datasciences are used in a bigdata world.

Professor Baesens will be present at the Data Innovation Summit on March 26th in Brussels.

He will present his latest book about Big Data Science.

Join us, you can get your free full day access pass when you  answer the Data Innovation Survey 2015.

Enjoy the webinar …

Join our next event

Please register using this meetup page:

Summit: Data Innovation Summit – Made in Belgium

Thursday, Mar 26, 2015, 8:00 AM

AXA building
boulevard du Souverain, 25 Watermael-Boitsfort, BE

450 Business & Data Science pro’s Attending

Toon Vanagt- Laurent Fayet – Filip Maertens – Kris Peeters – Vincent Blondel –David Martens – Hans ConstandtThe Data Innovation Summit in Brussels is a one day conference gathering all the Belgian actors facilitating data innovation. It is an action packed conference where more than 50 speakers will demonstrate what they do that helps us compete i…

Check out this Meetup →

Telecom Meetup was a hit – 173 registrations – Full aula @ VUB – Happy crowd

 

 

Thank you Jan, Renaud and Wim for the excellent presentations, thank you Gautier for orchestrating this event.

Latest news from our community by Philippe Van Impe – slides

Overview of data Science in the Telecom Industry and speakers introduction

Moderator: Gautier Krings – Head of Research @ Real Impact Analytics

  • Jan Sonck – Head of Enterprise Innovation @ Proximus – slides
    How do we use Data Science in a Telecom Operator?
    All Posts
    Example of external use cases: which business question, which data? What about privacy concerns?
  • Renaud Lambiotte – Assistant Professor @ FUNDP – slides 
    Social networks, from Granovetter to Zuckerberg 
  • Wim Hellemans – Head of Knowledge @ Real Impact Analytics
    How to convert Telecom data into insights?
    What are the benefits and challenges of processing telecom data.

Pictures of the event are available here .

Introduction slides here:

 

 

 

Job – UGent – Professor Statistics and Stochastic Modeling at Ghent University Global Campus (Incheo, South-Korea)

Ugent

Ghent University Global Campus (Incheon, South-Korea) has a vacancy for a professorship, starting from August 1, 2015. It concerns a full-time (100%) position as a professor in a rank (lecturer, senior lecturer or full professor) depending on the specific profile of the candidate. The candidate will be charged with academic teaching (in English) and scientific and academic duties.

Ghent University Global Campus invites applications from candidates with research programs in Statistics and Stochastic Modeling applied to the life sciences, specifically to Molecular Biotechnology, Environmental Technology and Food Technology

The candidate is expected to teach two courses in Statistics in the bachelor years and will in a later stage also teach two specialized related courses in the higher years of the bachelor or master programs. There is also the possibility of getting involved in the informatics training of the life science students. We expect the candidate to engage in the build-up of a data analysis research unit, in collaboration with colleagues and fellow professors at Ghent University Global Campus and related research groups at Ghent University in Belgium.
Ghent University Global Campus offers a five-year contract with a 90 % appointment at the Global Campus in Korea and a 10 % appointment at Ghent University, Belgium. This contact is renewable. The terms of employment at Ghent University Global Campus are comparable to European institutions and will be negotiated on an individual basis. Attractive incentives to relocate and a competitive research start-up package will be provided. Review of applications will begin by March 16, 2015. Review of applications will begin March 16, 2015.

Applicants

Profile

  • Candidates hold a PhD degree in statistics or related discipline with relevant experience at the moment of application;
  • Candidates have at least two years of post-doctoral experience at the time of appointment;
  • Candidates are experienced in statistical modeling and data analysis relevant to the life sciences, e.g. in Statistical Genomics, Environmental Statistics, High Dimensional Data Analysis and/or Statistical Process Control, which is proven by recent publications in national and international peer reviewed journals and/or books, and by presentations and contributions on national and international scientific meetings;
  • Candidates show sufficient knowledge and experience in applying statistics to teach basic courses in this discipline for the life sciences;
  • Candidates have the necessary didactical, organizational and communicative skills for teaching at an academic level;
  • Candidates have the drive to build a statistical research unit in collaboration with colleagues at Ghent University Global Campus and related groups at the Ghent University home campus. The unit will serve as a local point of reference for statistical methods development, design and analysis of empirical research in the life sciences;
  • To have experience with R/bioconductor, Python, Java or other relevant software packages and/or Big data hard and software will be considered an asset;
  • To have experience in leading research projects and/or coaching PhD students will be considered an asset;
  • To have international academic experience will be considered an asset.

Ghent University Global Campus is the first campus of Ghent University outside Belgium. This brand new campus is situated in Incheon, South-Korea. At the Global Campus Ghent University will offer 4-year bachelor and 2-year master programs in Molecular Biotechnology, Environmental Technology and Food Technology. Its programs are accredited in Flanders and in Korea. The granted degrees will be Ghent University degrees. The Ghent University Global Campus integrates educational and research facilities in a single building. Ghent University has the ambition to organize a first-rate, truly European education in Asia and to develop excellent research in the three above-mentioned fields.

More detailed information on teaching, research and academic tasks can be obtained from Prof. Els Goetghebeur (Els.Goetghebeur@UGent.be; +32 9 264 48 11) and Prof. Lieven Clement (Lieven.Clement@UGent.be; +32 9 264 49 04) . More detailed information about Ghent University Global Campus and the application procedure can be obtained from Dr. Thomas Buerman (Thomas.Buerman@ugent.be; + 82 32 626 4100).

More Jobs ?

Meetup – DataScience & Telco – February 19th – Brussels

meetup

 

How often do you use your mobile phone every day?

Yes, the telecom industry is one of the richest in terms of customer data!

This gold mine of data has led telecom operators to be at the forefront of Big Data applications and has attracted leading researchers from the academic world. This session will reveal how these exceptional data sources can be leveraged, from 3 different points of view: the telecom operator, the academia and the telecom Big Data solution provider.

Join us to understand why the telecom industry is attracting so many data scientists.

Agenda

18h30 – Opening

Update on the activities of the community

– Doing the Data Science Moocs together
– Vitual Global Hackathon – HACKSKI
– Overview of the outstanding datascience vacancies in Belgium
– Agenda of coming events, trainings, …

Introduction by moderator

Overview of data Science in the Telecom Industry and speakers introduction

Moderator: Gautier Krings – Head of Research @ Real Impact Analytics

  • Jan Sonck – Head of Enterprise Innovation @ Proximus
    How do we use Data Science in a Telecom Operator?
    Example of external use cases: which business question, which data? What about privacy concerns?
  • Renaud Lambiotte – Assistant Professor @ FUNDP
    Social networks, from Granovetter to Zuckerberg 
  • Wim Hellemans – Head of Knowledge @ Real Impact Analytics
    How to convert Telecom data into insights?
    What are the benefits and challenges of processing telecom data.

21h00: Open Sessions

Attendants are invited on the spot to share in a few minutes interesting DataScience issues they have  encountered in the last month. Recent startups, other meetup groups and teamleaders recruiting experts are welcome to do their pitch.

21h30: Networking @ KultuurKaffee

 

Register on the Meetup page please.

Data Sciences in the Telecom Sector

Thursday, Feb 19, 2015, 6:30 PM

VUB – Aula QB
Pleinlaan 2B – 1050 Brussels, BE

90 Business & Data Science pro’s Attending

How often do you use your mobile phone every day?Yes, the telecom industry is one of the richest in terms of customer data!This gold mine of data has led telecom operators to be at the forefront of Big Data applications and has attracted leading researchers from the academic world.This session will reveal how these exceptional data sources can b…

Check out this Meetup →

 

 

Webinar – Bart Baesens – State of the Art in Credit Risk Analytics

Bart Baesens   Professor of Big Data & Analytics

   https://lnkd.in/d2UQEzU

more about Bart on : http://www.dataminingapps.com/

 

 

 

Job – PhD Vacancy – LIRIS – Process Mining

KULeuven-logo-2012
Prof. Dr. Jochen De Weerdt has a PhD Vacancy – Process Mining (expected)
Jochen De Weerdt  I am looking for a PhD candidate in the area of Process Mining. Within the Leuven Institute for Research on Information Systems (LIRIS), you will be conducting research in an upcoming field that is situated at the intersection of business process management and data mining. For more details, see pdf-file below.

Vacancy – Process Mining

Download File

Project

The PhD will be doing research on the topic of Process Mining. Process mining techniques focus on process
discovery (extracting process models from event logs), conformance checking (comparing normative models
with the reality recorded in event logs), and extension (extending models based on event logs). It is a fastgrowing
field at the intersection of the business process management and data mining fields. From a
business viewpoint, process mining mainly has an edge in terms of objectivity because it allows to extract
business process knowledge from organisational data rather than going through the cumbersome and errorprone
process of interviews, workshops, etc. As such, process mining is gaining lots of traction in industry
because it is an excellent approach for driving business process improvements.
The LIRIS research group has plenty of experience with research in this area as demonstrated by several
ongoing and completed PhD projects in this area. Concretely, you will work on topics ranging from trace
clustering, active learning-based process mining, predictive process mining, conformance checking, to
hybrid process modelling and mining. You will develop prototype software implementations and will be
able to demonstrate their usefulness in practical settings through use cases in collaboration with industry
partners.

Training – KULeuven – Data Science in Practice – 5-6 February 2015

Data Science in Practice

INTRODUCTION

Modern information and communication technology is increasingly capable of collecting and generating large amounts of data that need to be analyzed to become useful or profitable. In fact, these amounts quickly become too large for immediate human understanding, leading to a situation in which “we are drowning in data but starved for knowledge”.

Data science represents an essential technology to transform such data into knowledge. It allows the automated discovery of interesting regularities or anomalies in large databases, thereby surpassing standard statistical summarizing. Typical tasks include the construction of predictive and descriptive models for classification, regression, clustering, associations, and probabilistic inference.

The DTAI research group of the department of Computer Science, KU Leuven, presents a course that provides a gentle introduction to data science for professionals who need to analyze data themselves, interpret results obtained using data science techniques, or give guidance to data analysts. The course introduces the principles, techniques and methodology of data science. It provides the attendants with an overview of the wide variety of data science techniques available, insight in which techniques are useful for what kind of tasks, expertise with practical data science tools, and real-life case studies.

The target audience of this course consists of professionals who experience a need for a better understanding of data science: which tasks can be solved, which techniques can be used, which are their strengths and weaknesses.

IMPORTANT DATES

Registration deadline: 20 January 2015
Course: 5-6 February 2015

Click here to register.

More info: http://dsip.cs.kuleuven.be/

 

 

European Presentation – Prof R. Zicari from Goethe University of Frankfurth – Bigdata & datadriven society

Roberto Zicari

Profesor Roberto V. Zicari (@odbmsorg), from the Goethe University  in Frankfurt recently gave a talk at Stanford on Big Data: http://ee380.stanford.edu

This is a very original presentation where bigdata is viewed from an European perspective: Big data a Data driven society

It contains information on the projects around  data driven innovation  from the European Commission.

If you are interested, this is the page with a link to download the presentation: http://www.odbms.org/2014/07/big-data-a-data-driven-society/

and you can watch the video on Youtube: http://www.youtube.com/watch?v=IBhu2kkZXGQ

New e-learning course Credit Risk Analytics by professor Bart Baesens

Baesens_Bart_small     Big Data World

Beste mensen van de Brussels Data Science Community,
Na 6 maanden werk eraan, is het zover!
Mijn E-learning cursus staat online op:
Laat gerust weten als je nog vragen zou hebben.
Vriendelijke groeten,
Bart

Prof. Dr. Bart Baesens
Faculty of Economics and Business
KU Leuven
Naamsestraat 69
B-3000 Leuven
Belgium

www.dataminingapps.com

Master of Information Management

————–

New e-learning course Credit Risk Analytics by professor Bart Baesens

The outline of the course is as follows:
Lesson 1: Introduction to Credit Scoring
Lesson 2: The Basel Capital Accords
Lesson 3: Preparing the data for credit scoring
Lesson 4: Classification for credit scoring
Lesson 5: Measuring the Performance of Credit Scoring Classification Models
Lesson 6: Variable Selection for Classification
Lesson 7: Issues in Scorecard Construction
Lesson 8: Defining Default Ratings and Calibrating PD
Lesson 9: LGD modeling
Lesson 10: EAD modeling
Lesson 11: Validation of Credit Risk Models
Lesson 12: Low Default Portfolios
Lesson 13: Stress testing
You are invited to send an email to Bart.Baesens@gmail.com if interested in more information.