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project help build a portfolio forces you to do analysis (usually) and communicate your results more interesting to grade than an exam

INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS

Course Project: Your Only Assignment

Why a Project

  • A project help build a portfolio
  • It forces you to do analysis (usually) and communicate your results
  • Far more interesting to grade than an exam

“It doesn’t matter how great your analysis is unless you can explain it to others: you need to communicate your results.”

R for Data Science

Hadley Wickham & Garrett Grolemund

General Project Guidelines

  1. Find a Data Source and Analyze it
    • You can search Kaggle or other dataset repositories)
    • Work*
    • Make your own
      • Use an API (like the twitter API) to gather data (Not easy)
      • Web Scraping (hard)
    • Improve on Previous Analysis Projects
  2. Other Python related options (pick any)
    • Code a ML Algorithm from scratch
    • Improve a Python project from another class (doesn’t have to be analysis related)
    • Translate your old code to Python

General Project Guidelines

  • Choose option A or B

 

Grading

  • Due to the nature of data analytics being a bit subjective and people being able to choose between different project options, anyone who turns in a project will get an A (95%) in this
  • Students may get up to an A+ (100%) if the project is
  • I will still provide feedback and areas for improvement on your

General Project Advice Option A

  • The following couple of slides are just

Option A: Task 1

  • Make a problem statement
  • After picking your dataset, it is important to figure out what problem you are trying to

 

Option A: Task 2

  • Identify who may use your result
  • In other words, figure out what is the potential usefulness of your analysis

 

Option A: Task 3

  • Make some preliminary goals for your project (what may come out of your work)

 

Option A: Task 4

 

  • Think of some Success Metrics for your analysis
    • For machine learning tasks, accuracy can help
    • Hypothesis Testing
  • How do we know it works/improves

Option A: Task 5

  • Mention any uncertainty/risks that may be a challenge to complete your
    • Example: For machine learning tasks, it helps to have more than 250

 

Option B

  1. Python related options (pick any)
    • Code a ML Algorithm from scratch
    • Improve a Python project from another class
    • Translate your code to Python

 

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