Data Science Boot Camp
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The Boot Camp is largely based on the contents of my recently published book, Getting Started with Data Science: Making Sense of Data with Analytics. You can read more about the book by Clicking HERE.
Logistical details:
When: Fridays (2:00 – 5:00 pm)
Where: 55 Dundas Street West, Toronto, 9th floor, Room 3-109
Ted Rogers School of Management, Ryerson University
Cost: Free (Courtesy Ryerson University & BigDataUniversity)
Starting on: May 13 for introductions. Actual launch is on May 20.
Spaces: I’d like to cap enrollment at 15.
Registration: Email us or use Registration Form at BigDataUniversity.
Prerequisites: Curiosity, high-school math, prescribed book, a laptop computer, and willingness to learn R.
BigDataUniversity will live stream the sessions for those who are unable to attend, but interested in the topic.
Tentative Schedule
- Detailed hands-on examples of analytics to understand what you will be able to accomplish by the end of the boot camp.
Week 2 – Data: It’s shapes, sizes, and formats
Week 3 – Regression: The tool that fixes everything, or almost everything.
- Applied analytics with teaching evaluations.
- Do good-looking instructors get higher teaching evaluations?
Week 4 – Correlations, causations, and manufactured facts
Week 5 – Aerobics with data: Taming your data to meet your needs.
Week 6 – Time is money: Analytics with time series data.
Week 7 – Case study 1:
- Do women who lack health insurance from their spouse’s employer more likely to work full-time?
Week 8 – Case Study 2:
- Do higher taxes result in lower cigarette sales? Did Land Transfer Tax impact housing sales in Toronto?
Week 9 – Case Study 3:
- To smoke or not to smoke: that is the question.
Week 10 – Case study 4:
- Is space the new frontier? Map it to know it.
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