Projects

Materials for the Project in COGS108.

Project Documentation

• Project Guidelines
• Team Policies

Project Templates

• Proposal
• Checkpoint #1: Data
• Checkpoint #2: EDA
• Final Project

Final Project Checklist

Students often ask for a rubric. You can use this checklist to help guide your thinking on the final project. If you check off all the boxes below, you should be in good shape to get a perfect score on your final project.

Overview, Question & Background

Overview:

• Write a clear summary of what you did
• Briefly describe the results of your project
• Limit overview to 3-4 sentences

Research Question:

• Include a specific, clear data science question
• Make sure what you're measuring (variables) to answer the question is clear

Background & Prior Work:

• Include a general introduction to your topic
• Include explanation of what work has been done previously
• Include citations or links to previous work

Hypothesis:

• Include your team's hypothesis
• Ensure that this hypothesis is clear to readers
• Explain why you think this will be the outcome (what was your thinking?)

Dataset(s):

• Include an explanation of dataset(s) used (i.e. features/variables included, number of observations, information in dataset)
• Source included (if outside dataset(s) being used)

Data Analysis:

Data Cleaning & Pre-processing

• Perform Data Cleaning and explain steps taken OR include an explanation as to why data cleaning was unnecessary (how did you determine your dataset was ready to go?)
• Dataset actually clean and usable after data wrangling steps carried out

Data Visualization:

• Include at least three visualizations
• Clearly label all axes on plots
• Type of all plots appropriate given data displayed
• Interpretation of each visualization included in the text

Data Analysis & Results:

• EDA carried out with explanations of what was done and interpretations of output included
• Appropriate analysis performed
• Output of analysis interpreted and interpretation included in notebook

Privacy/Ethics Considerations:

• Thoughtful discussion of ethical concerns included
• Ethical concerns consider the whole data science process (question asked, data collected, data being used, the bias in data, analysis, post-analysis, etc.)
• How your group handled bias/ethical concerns clearly described

Conclusion & Discussion:

• Clear conclusion (answer to the question being asked) and discussion of results
• Limitations of analysis discussed
• Does not ramble on beyond providing necessary information

Video:

• Question asked is clear to listeners
• Effective visualizations presented
• Clear explanations throughout
• Take home message clear
• Within 3-5 min time limit

Final Checks:

• Edit all text for clarity
• Remove all instructions
• Be sure text included throughout to guide reader
• Check to make sure all text and images are visible
• Names included
• Renamed file : FinalProject_groupXXX.ipynb, where 'XXX' is replaced by your group's group number