1. DO WE SUFFER A DATA SCIENCE
KNOWLEDGE GAP?
Bart Hamers, BDSC
2. DATA SCIENCE GAP?
• Belgian companies want to
integrate in data science in their
existing operations for efficiency or
to explore new business
opportunities .
• Data science needs a very specific
knowledge and environment to be
a success !
• Do we have data science expertise
in Belgium?
Yes,… we have everything it needs!
4. We have a long standing tradition in top research in
(applied) statistics and artificial intelligence!
Pattie Maes,
MIT Media
Laboratory
Luc Steels,
AI Lab,
SONY
Computer
Science
Laboratory
Ingrid
Daubechies
, Princeton
and Duke
University
Luc
Devroye,
McGill
Paul
Embrechts,
Swiss Fed.
Institute of
Technology
And… I ran out of place…
BELGIAN EXPERTISE
5. ACADEMIC PROGRAMS
IN BELGIUM
University of Brussels
• Master of Science in de
ingenieurswetenschappen:
computerwetenschappen
University of Antwerp
• Master in computer science with a
specialization in data science: profile
Artificiële Intelligentie
University of Gent
• Master of Science in Marketing Analysis
• Marketing Engineering
• Master of Science in Statistical Data
Analysis
University of Leuven (KUL)
• Master of Artificial Intelligence
• Master of Financial and Actuarial
Engineering
• Master of Statistics
• Master of Bioinformatics
University of Leuven (UCL Louvain-La-Neuve)
• Master in Statistics
University of Liege
• Master in Statistics
Solvay Business School
• Master in Quantitative Finance
Vlerick Business School
• Executive master class creating business
value with big data.
Transnational University Limburg – Hasselt -
Maastricht
• Artificial Intelligence
• Master of Statistics
15 programs training data scientists…
8. WHAT IS NECESSARY TO
LEARN DATA SCIENCE?
Bart Hamers
be.linkedin.com/in/hamersbart
Editor's Notes
Story of discussion Bart-Philippe on Data Science in Belgium!?
S: Belgian companies are interested in Data Science
C: Data Science is needs knowledge and special environment.
Q: Do we have this in Belgium
A: After working for the last 20 years in Data Science, both academically and in business (financial world), I am convinced we have everything necessary.
What is the perfect cocktail for a data science success?
Good data science research generating the idea’s for future business opportunities.
Good trained data scientist that can implement the new technologies
Skills developed through experience.
A Business environment the picks up new opportunities. (see ignite sessions of today)
Data Science enthusiasm and networking: BDSC
Good tradition of data scientists (statisticians, AI researchers,…)
Luc Steels:
pioneer AI
AI Lab VUB
Founder Computer Science Lab Sony Paris: Aibo Robot
Pattie Maes
Prof MIT!
MIT AI lab
Collaborative filtering, human-computer interfaces
Elected: One of the most Influential women in IT
I. Daubechies:
Princeton
Wavelets
Fingerprint analysis
P. Embrechts
Risk and Actuarial sciences -> banking regulations
L. Devroye
McGill Canada
Statistical learning theory -> mathematical foundations of statistics and machine learning
Co-autor with Vapnik, father of support vector machines
Belgians are to modest, Belgian engineers are at the same level of their MIT colleagues.
15 top level programs in data science… broad interpretation
Almost each Belgian University has a program.
Many foreign student attending the courses in Belgium
Perfect foundations for the future data scientists.
I feel frustrated when I see this slide…
Do we needs all of this in one person… NO!
data science is teamwork.
Analogy with languages in open vacancies.
You do not need to know all of them
Make sure you understand the other languages.
Overview of Skills
Current academic program certainly fill in all math & statistics skills!
Programming & data base, including visualization skills
Universities start to include them in their course program
Private companies are bridging the gap. (Online Training: ex: DataCamp)
Communication, domain knowledge and soft skills
Under represented in training courses
Very importing for the success of a data science project!
Conclusion: more attention should be give to the last (soft) skills.
experience
Training
BDSC want to play a role: please setup courses, share experience, and practice!
BDSC can and will help your facilitating
Importance of experience!
Learning is knowledge development AND skill development
Turn Passive Learning into active learning!
Therefore for:
data scientists
Join hackathons
Join data4good or open data initiatives
Share experience: give presentations
Network
Companies:
Setup POCs
Start as early as possible!
Gain experience
Give employees the environment to learn and experiment.
Open up your data for research and hackathons