Bdsc summit v1.0
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Bart Hamers discusses whether Belgium suffers from a data science knowledge gap. While Belgian companies want to integrate data science into their operations, data science requires specific expertise. However, Belgium has everything it needs - there is a long tradition of top research in statistics and AI, and 15 academic programs training data scientists. Belgium has expertise in data science skills and the necessary academic training to learn data science.
Bdsc summit v1.0
- 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!
- 3. PERFECT COCKTAIL Data Science Enthusiasm Business Opportunities Skills High level academic training Research
- 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…
- 6. SKILLS OF A DATA SCIENTIST!
- 7. WHAT IS NECESSARY TO LEARN DATA SCIENCE?
- 8. WHAT IS NECESSARY TO LEARN DATA SCIENCE? Bart Hamers be.linkedin.com/in/hamersbart
Editor's Notes
- #3: 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.
- #4: 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
- #5: 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.
- #6: 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.
- #7: 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
- #8: 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