DataDive 101 (Data Munging)
Details
Welcome to the first of our DataDive 101 series, which is to help prepare our data volunteers to handle the data of the social-good organizations we are helping!
130pm - 145pm: Networking
145pm - 2pm: Intro to datadive 101, soft intro to tools like tabula, openrefine and github (demo): Kai Xin
2pm - 2.15pm: Intro to R (hands on): Hansheng
2.15pm - 2.25pm: Break
2.25pm - 2.45pm: Getting and Cleaning Data with R part1 (hands on): Eugene
2.45pm - 3.05pm: Getting and Cleaning Data with R part2 (hands on): Shubham
3.05pm - 3.15pm: Break
3.15pm - 3.35pm: Cleaning difficult data (hands on or demo only): Viktor
3.35pm - 4pm: End of event / networking
Bio of trainers
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Kai Xin THIA is the Co-Founder of DataKind SG & DataScience SG. He is a Data scientist, ranking top 1,000 out of 190,000+ participants on Kaggle and Certified EMC Data Scientist Associate. He currently works at Khoo Teck Puat Hospital's Healthcare Analytics Unit.
Linkedin: http://sg.linkedin.com/in/thiakx/
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HanSheng has a double-degree Master in Knowledge Engineering (Computational Intelligence) and Electronics & Computer Engineering. He is a senior software engineer with 10 years of experience developing commercial-quality software components and software systems; adept at machine learning, pattern recognition, analytics, optimization, and embedded systems.
Linkedin: http://sg.linkedin.com/in/hschiu
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Eugene Teo holds Bachelor's and Master's degrees in Computing from the National University of Singapore. Eugene is Senior Manager at Symantec Security Response, and an adjunct lecturer at a local university. Eugene is passionate about data science.
Linkedin: http://sg.linkedin.com/in/eugeneteo
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Shubham Goyal has a bachelor of Computing (Computer Science) from the National University of Singapore. Passionate about Algorithms, Artificial Intelligence, Parallel Computing and Software Engineering.
Linkedin: https://www.linkedin.com/profile/view?id=99085809
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Viktor Gal is an engineer at Gravity R&D, an almost Netflix prize winner company and a small startup that's working on it's own recommendation engine for e-commerce and media.