Materials and outlines for the Final Project for COGS108.
Carefully read through all the details you'll need to know for your COGS108 Final Project.
- Option 1: Group (pdf here)
- Option 2: Individual (pdf here)
Due Friday, Oct 23 (11:59 PM)
Due Wed, Dec 16 (11:59 PM) - Finals Week
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:
- Write a clear summary of what you did
- Briefly describe 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 question is clear
Background & Prior Work:
- Include 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?)
- 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 Cleaning & Pre-processing
- Perform Data Cleaning and explain steps taken OR include 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 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
- Thoughtful discussion of ethical concerns included
- Ethical concerns consider the whole data science process (question asked, data collected, data being used, bias in data, analysis, post-analysis, etc.)
- Clear conclusion (answer to the question being asked) and discussion of results
- Limitations of analysis discussed
- Does not ramble on beyond providing necessary information
- Edit all text for clarity
- Remove all instructions
- Check to make sure all text and images are visible
- Names and IDs included
- Renamed file :
- Option 1:
FinalProject_groupXX.ipynb
, where 'XX' is replaced by your group's group number - Option 2:
FinalProject_GH.ipynb
, where 'GH' is replaced by your GitHub Username
- Option 1: