Week 0: Introduction & logistics

The agenda for May 13, 2016.
  1. Introductions
    1. Who are you?
    2. Why are you here?
    3. What would you like to learn?
    4. What do you know already?
    5. You MUST fill out our brief Survey. Click HERE for survey.
  2. Why data science? Why now?
  3. Key features of the boot camp:
    1. Informal
    2. Semi-unstructured
    3. Learner driven: BYOL, BYOD
    4. Platform agnostic
  4. What do you need?
    1. Curiosity, lots of it
    2. A puzzle
    3. A book: Getting Started with Data Science
      1. E-text, click HERE
      2. Printed version, click HERE.
    4. Software: I'll teach R
      1. How do we get R? Click HERE.
      2. How to learn R? Click HERE.
      3. Data Scientist Work Bench, Click HERE.
      4. Google Docs, collaborative writing
  5. What do you need for the next week
    1. Have R and R Commander installed on your device
    2. Come prepared with the required readings.
      1. Hamermesh, Daniel S. and Amy M. Parker (2005). "Beauty in the Classroom: Instructors' Pulchritude and Putative Pedagogical Productivity," Economics of Education Review, August 2005. pp. 5-16. 
    3. Weekly projects with a collective deliverable.
      1. Every data science project ends with a deliverable
      2. Deliverable: Tables, graphs, and a narrative
      3. We need a weekly puzzle
        1. Do shoppers on bikes spend more than those on cars?
        2. Data sources: ICPSR, Data librarians, 

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