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Community Data Science Course (Spring 2017)
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== Assignments == The assignments in this class are designed to give you an opportunity to try your hand at using the technical skills that we're covering in the class. There will be no exams or quizzes. There will be weekly assignments that I will ask you to hand-in but will only be graded as ''complete/incomplete''. Like many technical subjects, Data Science tends to build on earlier ideas, so I strongly suggest that you devote time to assignments every single week. === Final Project Idea === :'''Maximum Length:''' 600 words (~2 pages double spaced) :'''Due Date:''' Week 3 In this assignment, you should identify an area of interest, at least 2 sources with relevant data, and at least 3-4 questions that you plan to explore. I am hoping that each of you will pick an area that you are intellectually committed to and invested in (e.g., in your business or personal life). You will be successful if you describe the scope of the problem and explain why you think the data sources you've identified are relevant. I will give you feedback on these write-ups and will let you each know if I think you have identified a questions that might be too ambitious, too trivial, too broad, too narrow, etc. In week 2, we will walk through successful projects from previous course offerings to give you an idea of the correct scope. === Final Project Proposal === :'''Maximum Length:''' 1500 words (~5 pages) :'''Due Date:''' Week 7 This proposal should focus on two questions: * Why are you planning to do this analysis? Make sure to introduce any background information about the topic, the community, your business, or anything else that will be required to properly contextualize your study. * What is your plan? Describe the data sources will you collect and how they will be collected. Are there any blind spots given the data you have available? Are there any visualizations or tables that you plan to build? Your proposal should frame your final analysis, but it's also a chance to "sanity check" your plan. I will give you feedback on these proposals and suggest changes or modifications that are more likely to make them successful or compelling. I will also work with you to make sure that you have the resources and support necessary to carry out your project successfully. Be as specific as possible about the data available on the sources you've chosen. I expect that you will have written at least some of the final code that you will use in this course. Identify the documentation and the API endpoints where required. If there are libraries that you think may help with access, note them. === Final Project === :'''Presentation Date:''' Last week (date tbd) :'''Paper Due Date:''' Last meeting plus 7 days. For your final project, I expect you to build on the first two assignments to describe what they have done and what you have found. I'll expect every student to give both: # A short presentation to the class (10 minutes) # A final report that is not more than 4500 words (~18 pages) I expect that your reports will include text from the first two assignments and reflect comprehensive documentation of your project. Each project should include: (a) the description of the question you have identified and information necessary to frame your question, (b) a description of the how you collected your data, (c) the results, (d) a description of the scope or limitations of your conclusion. A successful project will tell a compelling, defensible story in prose and plots and will contain source code sufficient to reproduce the results. ==== Paper and Code ==== Your final project should include detailed information on: * The problem or area you have identified and enough background to understand the rest of your work and its importance or relevance. * Your research question(s) and/or hypotheses. * The methods, data, and approach that you used to collect the data plus information on why you think this was appropriate way to approach your question(s). * The results and findings including numbers, tables, graphics, and figures. * A discussion of limitations for your work and how you might improve them. If you want inspiration for how people use data science to communicate this kinds of findings broadly and effectively, take a look at great sources of data journalism including [http://fivethirtyeight.com/ Five Thirty Eight] or [http://www.nytimes.com/upshot/ The Upshot at the New York Times]. Both of these publish a large amount of excellent examples of data analysis aimed at broader non-technical audiences like the ones you'll be communicating with and quite a bit of their work is actually done using Python and web APIs! A simple Five Thirty Eight story will include a clear question, a brief overview of the data sources and method, a figure or two plus several paragraphs walking through the results, followed by a nice conclusion. I'm asking you to try to produce something roughly similar. Keep in mind that most stories on Five Thirty Eight are under 1000 words and I'm giving up to 4,500 words to show me what you've learned. As a result, you should do ''more'' than FiveThirtyEight does in a single story. You can ask and answer more questions, you can provide more background, context, and justification, you can provide more details on your methods and data sources, you can show us more graphs, you can discuss the implications of your findings more. Use the space I've given you to show off what you've done and what you've learned! Finally, you should also share with me the full Python source code you used to collect the data as well as the data set itself. Your code along will not form a large portion of your final grade. Rather, I will focus on the degree to which you have been successful at answering the ''substantive'' questions you have identified. At least 25% of your grade for this project will be determined by the visualizations and tables in your report. Good visualizations should "stand alone" and motivate the core results in your paper all by themselves. A good question to keep in mind is "could I tell this story with the visualizations and a tweet?" ==== Presentation ==== Your presentation should provide me with a very clear idea of what to expect in your final paper. However, don't treat it as a comprehensive overview of your paper: I would rather you tell a subset of the story well than the whole story in a rushed fashion. For instance, you can give a completely successful presentation by describing the motivation and walking through one plot in your paper. I'm going to give you all at least a paragraph of feedback after your talk. This will be an opportunity for me to see a preview of your paper and give you a sense for what I think you can improve. It's to your advantage to both give a compelling talk and to give me a sense for your project. ;Timing: All presentations will need to be '''a maximum of 7 minutes long'' with additional 2-3 minutes for questions and answers. Timing is going to be tight and I'm going to set an alarm and stop presentations that go too long. Concisely communicating an idea in the time allotted is an important skill in its own right. ;Slides: You are encouraged to use slides for your talk but I will need your slides ahead of class. See link at top of this section. Please keep in mind that your slides are meant to be additive, not a teleprompter. === Participation === The course relies heavily on participation. The material we're going to be covering is difficult and we're going to be covering it quickly. It is going to be extremely difficult to make up any missed classes. Attendance will be the most important part of participation and missing more than 1 class is going to make it extremely difficult to excel in our class. Nearly every week, we will begin by discussing challenges and problem sets that we'll define as a group at the end of the previous class. Please speak up and engage in this part of the class as well as asking questions anytime there is anything confusing. If you are feel confused about a new Python concept, it's highly unlikely that you are the only one. If there is anything I can do to help you participate in class, please let me know in the anonymous feedback. In general, my teaching style is more conversational than a formal lecture. I prefer that students feel they can "politely interrupt" at any time to seek clarification or make a well-informed point, and we keep the class small to encourage this. === Weekly Coding Challenges === Most weeks I will give you all a set of weekly coding challenges before the end of class that will involve changing or adding to code that I've given you as part of the projects in the final parts of class to solve new problems. These coding challenges will occasionally be turned in but will not be graded on effort not full correctness. I will share my solutions to each of the coding challenges in the subsequent class or via email. As you will see over the course of the quarter, there are many possible solutions to many programming problems and my own approaches will often be different than yours. That's completely fine! Coding is a creative act! Please do not share answers to challenges before midnight on Sunday so that everybody has a chance to work through answers on their own. After midnight on Sunday, you are all welcome and encouraged to share your solutions and/or to discuss different approaches. We will discuss the coding challenges for a short period of time at the beginning of each class.
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