Demystifying Data Science
We all know the description of the Data Scientist being “The Sexiest Job of the 21st Century”, but do you have a clear understanding of what Data Science actually is? Chiin and Alice Daish are at this month's LBAG to help us find the answer!
In this talk, Data Science practitioners Alice and Chiin will present experience-based insights that enable clarity about this undoubtedly red hot but nebulous trend, by sharing coherent definitions, frameworks, and facts that help clear up some of the key areas of confusion. They will outline their view of Data Science best-practices, common misconceptions, pitfalls, and practical tips for those looking to make a career transition. This talk will ultimately deliver awareness about the reality of the Data Science profession, and help demystify the hype.
YOU MAY ALSO LIKE:
- Fast Track to Machine Learning with Louis Dorard (in London on 21st - 23rd May 2018)
- Brian Sletten's Data Science with R Workshop (in London on 2nd - 4th July 2018)
- Infiniteconf 2018 - The conference on Big Data and AI (in London on 5th - 6th July 2018)
- Blockchain by Brian Sletten (in London on 9th - 10th July 2018)
Thanks to our sponsors
Demystifying Data Science
Chiin-Rui Tan
Chiin is the Head of Data Science at the Foreign & Commonwealth Office, leading the establishment of a new data science capability. She has an Economics degree from the University of Cambridge, and interest in applied microeconomics topics. Founder & Co-Founder of R-Ladies London & Global, Chiin is a keen R evangelist and active promoter of computing to underrepresented minorities. Professional specialisms include data-centric leadership, econometrics, digital analytics, visualisation, data democratisation, and strategic insight.
Alice Daish
Alice Daish is a Data Scientist with experience in using data for decision making and organisational data transformation. Previously working at The British Museum focusing on making the museum data-driven. Co-Founder of R- Ladies Global and Leadership Team. Microsoft MVP. Registered Scientist previously trained in ecology and quantitative biology.
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SkillsCast
We all know the description of the Data Scientist being “The Sexiest Job of the 21st Century”, but do you have a clear understanding of what Data Science actually is? Chiin and Alice Daish are at this month's LBAG to help us find the answer!
In this talk, Data Science practitioners Alice and Chiin will present experience-based insights that enable clarity about this undoubtedly red hot but nebulous trend, by sharing coherent definitions, frameworks, and facts that help clear up some of the key areas of confusion. They will outline their view of Data Science best-practices, common misconceptions, pitfalls, and practical tips for those looking to make a career transition. This talk will ultimately deliver awareness about the reality of the Data Science profession, and help demystify the hype.
YOU MAY ALSO LIKE:
- Fast Track to Machine Learning with Louis Dorard (in London on 21st - 23rd May 2018)
- Brian Sletten's Data Science with R Workshop (in London on 2nd - 4th July 2018)
- Infiniteconf 2018 - The conference on Big Data and AI (in London on 5th - 6th July 2018)
- Blockchain by Brian Sletten (in London on 9th - 10th July 2018)
Thanks to our sponsors
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About the Speakers
Demystifying Data Science
Chiin-Rui Tan
Chiin is the Head of Data Science at the Foreign & Commonwealth Office, leading the establishment of a new data science capability. She has an Economics degree from the University of Cambridge, and interest in applied microeconomics topics. Founder & Co-Founder of R-Ladies London & Global, Chiin is a keen R evangelist and active promoter of computing to underrepresented minorities. Professional specialisms include data-centric leadership, econometrics, digital analytics, visualisation, data democratisation, and strategic insight.
Alice Daish
Alice Daish is a Data Scientist with experience in using data for decision making and organisational data transformation. Previously working at The British Museum focusing on making the museum data-driven. Co-Founder of R- Ladies Global and Leadership Team. Microsoft MVP. Registered Scientist previously trained in ecology and quantitative biology.