data science

In partnership with Course Report, Metis Sr. Data Scientist Kimberly Fessel recently hosted a *Math for Data Science* webinar. During the 40-minute conversation, Kimberly highlights why you need math skills to be a Data Scientist and goes in-depth into which types of math you need to know in order to launch your career and find lasting success.

"Blending coding skills with math skills is the core of data science. The algorithms that we use in data science are all worded in mathematics," said Kimberly during the webinar. "Whether it's an optimization problem, probability problem, or scoring metrics – all of those things are going to require math skills to understand what's going on. Here’s an analogy I like to use to explain this concept: in order to drive your car, you don't necessarily need to know how it all works. But if you're going to be a professional mechanic, you have to know all of those component pieces. For data science, the components are math concepts."

She then goes over what she calls the "four core math concepts for Data Science," which are Linear Algebra, Calculus, Probability, and Statistics, discussing each in detail before providing sample problems (with solutions!) for each. For anyone interested in applying to a data science bootcamp, this webinar is sure to help them prepare.

Watch the full webinar on the **Course Report blog here**, where you'll also have access to Kimberly's Google Slides and a full transcript of the conversation.

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*Want more content from Kimberly? Check out her Metis blog post on How to Gather Data from YouTube here.*

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