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Deliverables due August 25 A 1-minute pitch for your solution. A 3-minute presentation of your group’s process from beginning to end including challenges you faced, lessons you learned, and any advice you have for future learners. A link to your presentation in your repository README. Complete the milestone survey. A retrospective for this milestone.
Overdue by 1 month(s)•Due by August 24, 2025•2/2 issues closedDeliverables due August 11 A document describing your target audience, their capabilities and constraints, how you intend to reach them, what you would like them to learn, and how you hope they will act. (Personas can be helpful!) A communication artifact to achieve the goals in your document. Let your imaginations run with this! It could be a website, a powerpoint, a printed leaflet, a WhatsApp campaign … anything, as long as you can justify why it’s the best way to reach them. Complete the milestone survey A retrospective for this milestone.
Overdue by 1 month(s)•Due by August 11, 2025•5/5 issues closedDeliverables due July 21 A non-technical explanation of your findings, including your levels of certainty and possible sources of error in your analysis. This should include visualizations. A technical description of your analysis & results including explanations of why you used the techniques you did, possible flaws in your analysis, and possible alternative approaches. All of the scripts and documentation necessary for someone to replicate your analysis using your data set. Complete the milestone survey A retrospective for this milestone
Overdue by 2 month(s)•Due by July 21, 2025•21/23 issues closedLearning objectives include: Understand the strengths and weaknesses of modeling the world using data. Learn to study a domain to understand which data is interesting and relevant for a given problem Investigate the data available in a domain to understand what is available, what is missing, what you could realistically collect yourself, and possible flaws in the data. Collect, clean, organize and document a data set so it is easy to study. Deliverables due June 30 A non-technical explanation of how you chose to model your domain, and possible flaws in this approach, in your README. (visuals can be very helpful!) Documentation for your data set describing where it came from, how it’s structured, possible flaws, and how someone can recreate it. Think broadly about data, qualitative data is still data! All of your data collection and cleaning scripts so someone can replicate your final data set given your raw data sources. This includes scripts for separating your data set into training and validation data, if applicable. A public hosting of your prepared data set. This can be directly in your repository, or a link to where it is hosted. Complete the milestone survey. A retrospective for this milestone.
Overdue by 2 month(s)•Due by June 30, 2025•11/12 issues closed