Using Statistics to Become a Better Data Scientist

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Presented by

Christopher Peter Makris, Lead Data Scientist at Dataiku

About this talk

As demand for the data scientist role remains high in 2021, the onus is on data scientists to find ways to differentiate themselves amidst a sea of competition and continuously expand their toolbelt. Many of today’s data scientists don’t have a formal statistics background, so learning statistics and probability concepts can be a value-add for them as they aim to increase their understanding of machine learning concepts, improve their models, and bring a new perspective to their projects. This talk, led by Christopher Peter Makris, lead data scientist at Dataiku, will cover key statistics concepts for data scientists to know and how they can be applied to everyday data science tasks.

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Dataiku is the world’s leading platform for Everyday AI, systemizing the use of data for exceptional business results. Organizations that use Dataiku elevate their people (whether technical and working in code or on the business side and low- or no-code) to extraordinary, arming them with the ability to make better day-to-day decisions with data. More than 450 companies worldwide use Dataiku to systemize their use of data and AI, driving diverse use cases from fraud detection to customer churn prevention, predictive maintenance to supply chain optimization, and everything in between.