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<P><STRONG>Learn about the Statistics background you'll need to work as a Data Scientist!</STRONG></P>
<P><STRONG>About the Event:</STRONG></P>
<P>Statistics underlie nearly every aspect of the work of a data scientist. We will use a straight-forward example of a data science challenge encountered by a San Francisco grocery delivery company to illustrate some key concepts in statistics. The company needs to accurately predict how much space an order will take up in a vehicle (in terms of number of bags) in order assign delivery routes efficiently. This problem is analogous to one that every grocery shopper faces: "do I have enough bags for all of my groceries?" -- Thus, it is a great jumping-off point for diving into some statistics.</P>
<P>You will learn about topics such as the Central Limit Theorem, and Bootstrap Aggregating, which come up as we go through the process of iteratively improving our predictions of the number of bags in an order. These subjects are just a few of the key elements of statistics that we cover in our 12-week, full-time Data Science Immersive program at Galvanize. Our language of choice for data science at Galvanize is Python and I will be using Python for demonstrating various results during the talk, but no prior experience with Python is expected of the audience.</P>
<P><STRONG>About the Instructor:</STRONG></P>
<P><STRONG></STRONG><A HREF="https://www.linkedin.com/in/bradleyajacobs" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Brad Jacobs</A>has apassion for exploring data springs from his experience studying millions of stars across hundreds of nearby galaxies observed with the Hubble Space Telescope. When not pondering galaxies Brad spent his time teaching astronomy in various classroom and outreach settings. After deciding to pursue work involving more earthbound datasets, he joined Cohort-1 (zero-indexed) of Zipfian Academy, the precursor to Galvanize's Data Science Immersive. Brad then went to work as a machine learning engineer at a consumer analytics startup before choosing to rejoin Galvanize as an instructor.</P>
<H3>Agenda:</H3>
<P>6:00pm Doors open, networking, snacking</P>
<P>6:20pm Lesson kick-off</P>
<P>7:45pm Final notes, open Q&A</P>
<P>8:00pm Conclusion</P>
<P><STRONG>About the Galvanize<A HREF="http://www.galvanize.com/courses/data-science/" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Data Science Immersive</A>:</STRONG></P>
<P>This program is for people who are serious about becoming data scientists. Over the course of 12 weeks you'll learn the tools, techniques, and fundamental concepts you need to know to make an impact as a data scientist. You'll work through messy, real-world data sets to gain experience across the data science stack: data munging, exploration, modeling, validation, visualization, and communication. Our unique setting in the Galvanize community of startups and tech companies is the perfect place to learn and expand your network!</P>
<P>If you have any questions about Galvanize's Data Science Immersive program before this event, please feel free to reach out to our Admissions Advisor, Victor, at<A HREF="mailto:victor.valdez@galvanize.com" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">victor.valdez@galvanize.com</A>.</P>
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