Lecture on the ways, in which data are being used in businesses to advance everything they do.

1. DATA SCIENCE IS A STATE OF MIND

2. ME
Bc in Applied Math (Masaryk University) / MSc Artificial Intelligence (Polytech Nantes)
Data Scientist at Kreditech / first Data Scientist at Ulmon (CityMaps2Go)
Co-Founder at Knoyd

3. KNOYD
Photo: Jamie Niederer (www.jamieniederer.com)

4. KNOYD
Founded by two alumni of Masaryk University (Czech Republic), born and raised in
Slovakia
Customized data solutions for businesses of any size
Trying to fill the hiring gap in data-job market

5. AGENDA
Evolution of productivity
Data vs. non-data management
Areas of application
How to become a Data Scientist

6. EVOLUTION OF PRODUCTIVITY

7. MAN MAKES TOOLS

8. MAN MAKES MORE TOOLS

9. TOOLS MAKE TOOLS

10. MACHINE MAKES TOOLS

11. MAN MAKES MEN

12. WHY SHOULD YOU CARE?

13. SPEED OF DEVELOPMENT

14. AMOUNT OF DATA
Internet live stats

15. JOB MARKET
“… the sexiest job of 21st century.”
Relative growth of # of Data Science jobs

16. JOB MARKET

17. DATA VS. NON-DATA MANAGMENT

18. MANUAL VS. AUTOMATION

19. INTUITION VS. VALIDATION

20. REACTIVE VS. PROACTIVE

21. EXPERT-ONLY VS. AUGMENTED

22. AREAS OF APPLICATION

23. Classification

24. Regression
Source: http://www.datapine.com/blog/big-data-and-ski-resorts/

25. Clustering
Source: https://2.bp.blogspot.com/-KS6-whrl9pM/Vr3fT6e51qI/AAAAAAAABfA/rVvPkY-N_14/s1600/neurokiff-tablettte.jpg

26. Recommender Systems
Source: http://www.slideshare.net/Hadoop_Summit/shah-june27-425pmroom210av2

27. Recommender Systems
Source: Nina Rabinowitz, Marijuana: Turn another leaf

28. Social Network Analysis
Barack Obama campaign

29. Text Analytics
Source: https://hsto.org/getpro/habr/post_images/8e4/768/568/8e47685686001174765c7b00bb4b8b44.png

30. Text Analytics
different text analytics functions
reinventing human resources

31. Deep Learning
Image captioning

32. Data Visualization
How parents’ income predicts college chances of children
Aging of the US population

33. KINDS OF DATA SCIENCE

34. UNICORN DATA SCIENTIST

35. TYPES OF DATA SCIENTIST
Source: http://www.marketingdistillery.com/wp-content/uploads/2014/11/mds_f.png
Research Scientist
Data Engineer
Visualization Expert
Data Manager

36. WHERE TO GET THEM

37. WHERE CAN YOU GET THEM
MOOCs: Coursera, EdX, Udacity
Bootcamps: DSR, Data Science Europe
Formal education

38. THE HARDEST PARTS

39. ASK THE RIGHT QUESTION: INTERESTING
“We run the company by questions, not by answers. So in the strategy process we've so far
formulated 30 questions that we have to answer […] You ask it as a question, rather than a
pithy answer, and that stimulates conversation. Out of the conversation comes innovation.
Innovation is not something that I just wake up one day and say 'I want to innovate.' I think
you get a better innovative culture if you ask it as a question.”
Eric Schmidt (Executive Chairman of Alphabet Inc. / Former CEO Google)

40. ASK THE RIGHT QUESTION: SOLVABLE
What data do you have?
What other data can you get? How? Where? Privacy?
Resources available?
Development burden vs. added value?

41. PITFALLS
Overfitting
Leakage
Class Imbalance
Missing Data / Outliers
!!! BIASES !!!

42. www.basecamp.ai

43. FUTURE IS DATA!
+43 681 323 82
linkedin.com/company/knoydwww.knoyd.com
lukas@knoyd.com
Web:
E-mail:
Phone:
facebook.com/knoyding
twitter.com/knoyd_com

44. ATTRIBUTIONS
Stefano Vetere, Ray Design, Sergey Patutin from the Noun Project
Nina Rabinowitz for “Marijuana: Turning the next leave”