Data Science: Capstone Rubric for Part 5

Data Science | Capstone, Part 5

Your project criteria were derived from the following standards, taken from our data science lifecycle:

• Frame The Problem
• Prepare and Explore Your Data
• Model
• Communciate

Acceptable performance for these standards is based on how well you’ve performed the specific requirements listed below.

Performance Evaluation

RUBRIC

| Score | Interpretation | | — | — | | 0 | Project fails to meet the minimum requirements for this item. | | 1 | Project meets the minimum requirements for this item, but falls significantly short of portfolio-ready expectations. | | 2 | Project exceeds the minimum requirements for this item, but falls short of portfolio-ready expectations. | | 3 | Project meets or exceeds portfolio-ready expectations; demonstrates a thorough understanding of every outlined consideration. |

REQUIRED

1. Host a 15-minute well-rehearsed presentation of your project for your audience.
   • Define technical terms and any basic data science concepts that inform your approach.
   • Don’t just deliver the information; tell a story about the problem and solution.
2. Prepare polished visuals and a publicly-suitable slide deck to guide your presentation.
   • Include graphs and/or visualizations.
3. Make sure you cover the following areas:
   • Goals
   • Success Criteria / Metrics
   • Data
   • Overall Approach
   • Basic description of model
   • Findings
   • Risks/Limitations
   • Impact, next steps, conclusions
4. Successfully answer questions about your project from, and for, your audience.

BONUS

1. Discuss longer term potential of your project and model.
   • Describe how you could validate your model’s performance over time
   • Explain how you would deploy your model in a production environment
2. Create a publicly hosted interactive visualization that your audience can use to further access and explore your data and findings.
   • Bonus points for embedding this into your blog post tutorial!