<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="http://www.r-bloggers.com/data-science-boot-camp/"></div></div><div><a data-url="http://www.r-bloggers.com/data-science-boot-camp/" data-counturl="http://www.r-bloggers.com/data-science-boot-camp/" data-count="horizontal" data-text="Data Science Boot Camp" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="http://ekonometrics.blogspot.com/2016/05/data-science-boot-camp.html"> eKonometrics</a></strong>, and kindly contributed to <a rel="nofollow" href="http://www.r-bloggers.com/">R-bloggers)</a> </div>
<div dir="ltr">If you live in or near Toronto, are interested in learning about data science, and can spare Friday afternoons, then you are in luck. I am offering a <a target="_blank" href="https://sites.google.com/site/statsr4us/workshops/datascience">Data Science Boot Camp</a> at <a target="_blank" href="http://www.ryerson.ca/tedrogersschool/bm/programs/real-estate-management.html">Ryerson University</a> in collaboration with IBM’s <a target="_blank" href="http://bigdatauniversity.com/">BigDataUniversity.com</a>. 
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<div><a target="_blank" href="http://www.ibmpressbooks.com/ShowCover.asp?isbn=9780133991024&type=f"><img src="http://www.ibmpressbooks.com/ShowCover.asp?isbn=9780133991024&type=f" border="0"></a></div>
<p>The Boot Camp is largely based on the contents of my recently published book, <i><a target="_blank" href="http://www.ibmpressbooks.com/store/getting-started-with-data-science-making-sense-of-data-9780133991024">Getting Started with Data Science</a>: Making Sense of Data with Analytics</i>. You can read more about the book by <a target="_blank" href="http://ekonometrics.blogspot.ca/2016/01/getting-started-with-data-science.html">Clicking HERE</a>.<br>
<h3>Logistical details:</h3>
<p><b>When</b>: Fridays (2:00 – 5:00 pm)<br><b>Where</b>: 55 Dundas Street West, Toronto, 9th floor, Room 3-109<br>     Ted Rogers School of Management, Ryerson University<br><b>Cost: </b>Free (Courtesy Ryerson University &amp; BigDataUniversity)<br><b>Starting on</b>: May 13 for introductions. Actual launch is on May 20.<br><b>Spaces</b>: I’d like to cap enrollment at 15.<br><b>Registration: </b><a target="_blank" href="mailto:murtaza.haider@ryerson.ca">Email us</a> or use <a target="_blank" href="http://bigdatauniversity.com/events/data-science-bootcamp-summer-data-analytics-insight/">Registration Form</a> at BigDataUniversity.<br><b>Prerequisites</b>: Curiosity, high-school math, prescribed book, a laptop computer, and willingness to learn R.</p>
<p>BigDataUniversity will live stream the sessions for those who are unable to attend, but interested in the topic.
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<h3>Tentative Schedule</h3>
<div><b>May 13, 2016</b>– Introductions, software details, and logistical details.</div>
<div><b>Week 1</b> – Taking the first step</div>
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<li>Detailed hands-on examples of analytics to understand what you will be able to accomplish by the end of the boot camp.</li>
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<p><b>Week 2</b> – Data: It’s shapes, sizes, and formats<br><b>Week 3</b> – Regression: The tool that fixes everything, or almost everything.
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<li>Applied analytics with teaching evaluations. </li>
<li>Do good-looking instructors get higher teaching evaluations?</li>
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<p><b>Week 4 </b>– Correlations, causations, and manufactured facts<br><b>Week 5 </b>– Aerobics with data: Taming your data to meet your needs.<br><b>Week 6 </b>– Time is money: Analytics with time series data.<br><b>Week 7</b> – Case study 1: </div>
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<li>Do women who lack health insurance from their spouse’s employer more likely to work full-time?</li>
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<p><b>Week 8</b> – Case Study 2: </div>
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<li>Do higher taxes result in lower cigarette sales? Did Land Transfer Tax impact housing sales in Toronto?</li>
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<p><b>Week 9</b> – Case Study 3: </div>
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<li>To smoke or not to smoke: that is the question.</li>
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<p><b>Week 10</b> – Case study 4: </div>
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<li>Is space the new frontier? Map it to know it.</li>
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