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<H2>*Note: This course costs $495 and meets for 4-weeks, Tuesdays & Thursdays, 6-7pm</H2>
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<DIV>Statistics for Data Science</DIV>
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<DIV>This course provides 8 lectures introducing probability, distributions, the frequentist/ Bayesian debate, statistics, inference/hypothesis testing, predictive modeling, and model assessment. We will use Python to illustrate the concepts, but no working knowledge of Python or any other language is required.</DIV>
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Who Should Take this Class?
People looking for an introduction to statistics in order to be better prepared for self study in data science; and people interested in gaining the skills required for admittance to the New York Galvanize Data Science Immersive. 
Prerequisites:
Desire to learn.
Setup: 
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<LI CLASS="m_-1839855201248594546gmail-li2">Bring your laptop and power cable</LI>
<LI CLASS="m_-1839855201248594546gmail-li5">Execute the instructions in the<A HREF="https://github.com/zipfian/python-fundamentals/tree/master/introduction" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Installation Guide</A>prior to day 1</LI>
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Weekly Agenda:
Tuesdays & Thursdays,6:00-7:00 pm
Full Course Outline:
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<LI CLASS="m_-1839855201248594546gmail-li2">Week 1:</LI>
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<LI CLASS="m_-1839855201248594546gmail-li2">First class: getting started</LI>
<LI CLASS="m_-1839855201248594546gmail-li2">Second Class: probability</LI>
</UL>
<LI CLASS="m_-1839855201248594546gmail-li2">Week 2:</LI>
<UL CLASS="m_-1839855201248594546gmail-ul2">
<LI CLASS="m_-1839855201248594546gmail-li2">First class: more probability</LI>
<LI CLASS="m_-1839855201248594546gmail-li2">Second Class: distributions</LI>
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<LI CLASS="m_-1839855201248594546gmail-li2">Week 3:</LI>
<UL CLASS="m_-1839855201248594546gmail-ul2">
<LI CLASS="m_-1839855201248594546gmail-li2">First class: Bayesian inference</LI>
<LI CLASS="m_-1839855201248594546gmail-li2">Second Class: statistics</LI>
</UL>
<LI CLASS="m_-1839855201248594546gmail-li2">Week 4:</LI>
<UL CLASS="m_-1839855201248594546gmail-ul2">
<LI CLASS="m_-1839855201248594546gmail-li2">First class: inference</LI>
<LI CLASS="m_-1839855201248594546gmail-li2">Second Class: predictive methodology</LI>
</UL>
</UL>
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Interested in the<A HREF="http://www.galvanize.com/courses/data-science/" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Galvanize immersive program in data science</A>? As part of the admissions process for the Data Science immersive program there are two interviews: Python and statistics. These materials survey the areas of probability and statistics that will be covered in the statistics interview. In addition to the overview there are resources for further study that are meant to reinforce the most important topics.You can submit your application<A HREF="https://new.galvanize.com/denver/data-science" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">here</A>.For more information visit the<A HREF="http://www.galvanize.com/faq/data-science" TARGET="_blank" REL="noopener noreferrer noopener nofollow noopener noreferrer nofollow nofollow noreferrer nofollow">Admissions data science FAQ page</A> 
Tuition Credit:100% of this part time course payment can be used as tuition credit for our Data Science Immersive program. Candidates must enroll in an immersive that beginswithin 1 yearof the completion of their part time course(s).