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DS2001 Programming with Data Social Science Practicum. Welcome!. Carolina Mattsson, Instructor mattsson.c@northeastern.edu. Syllabus. Section 2. Carolina Mattsson, Instructor Sarthak Bhandari, TA Wednesdays @ 9:50–11:30am West Village H 212

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Welcome!

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  1. DS2001 Programming with Data Social Science Practicum Welcome! Carolina Mattsson, Instructor mattsson.c@northeastern.edu

  2. Syllabus

  3. Section 2 Carolina Mattsson, Instructor Sarthak Bhandari, TA Wednesdays @ 9:50–11:30am West Village H 212 This course teaches hands-on programming skills using using applied examples drawn from the social sciences. We will also read/discuss how data science is impacting society, and work to develop an intuition for computational social science.

  4. Office hours Carolina Mattsson, Instructor Tuesdays @ 9:30–11:30am West Village H 164 or by appointment You are welcome to come to my office hours!

  5. Grading Weekly coding exercises (30%) Reading reflections (six) (15%) Class + Piazza discussion (15%) Final Project + Presentation (40%) It is important to attend every class. While I will not keep attendance, each class includes in-class coding exercises and discussions of the week’s readings. If you miss class, you lose the opportunity to get those points. Notify me ahead of time if you know you will miss class, with enough notice.

  6. Programming Exercises Weekly, completed in-class Submitted via Blackboard This is practice, you are learning a new skill. If you start finding it difficult to complete the exercises in-class, it may help you to come to office hours the day before. Note that learning to program is often challenging, but this is not because it is any more difficult than learning anything else – it is because coding often feels all-or-nothing!

  7. Assigned Reading • Weekly, completed before class • Reading reflections • 250-500 words, as a post on Piazza • Six in total, choose wisely • Due by midnight Tuesday • Class + Piazza discussion • Give everybody the space to talk • Respect one another’s thoughts

  8. Final Project • Project teams October 23rd • Project Proposal October 30th • Identify a question • Identify a source of data • Describe your techniques • Project Notebook November 27th • Project Presentation December 4th

  9. Motivation

  10. Programming is POWERFUL • Computing • Big Data • Big Digital Data Digital traces of our daily lives are increasingly recorded, aggregated, analyzed, and used to shape our future.

  11. Let’s get started!

  12. Hello World!

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