Project Description There Are Two Options For The Final Project Option I You Can

Project Description

There are two options for the final project:

Option I: You can conduct research on a topic related to Data Analytics, or Machine Learning. It is highly recommended that the topic is related to your research area of interest or on a recent/upcoming area of Data Analytics, Machine Learning or the umbrella field of Data Science in general. Your final deliverable will be formatted for submission to a conference. At this point, you should not worry about page limits as it will depend on the conference/cfp that is assigned to your topic.

Option II: Projects should involve analytics on actual data of a significant size. You will locate a dataset of choice, build/apply a model/algorithm, and then analyze the data. Remember that we will learn the process of modeling in this course. You are encouraged to use your tool (s) of choice. You will store your project work online in portfolio form to show proof of analytics work done. This will be very helpful for future purposes. The instructor must approve projects before you start working. 

You must submit a project proposal containing:

.

  • Option selected
  • If Option I: Topic of interest and a one page (double spaced) document explaining your interest in the topic with an outline of points you wish to address/research in this paper and the type of paper (Systematic Review, Meta-Analysis, or idea/opinion/editorial).
  • If Option II: Explore repositories of datasets available on the Internet. (Some examples are listed below):
    • www.kdnuggets.com
    • www.kaggle.com (Kaggle has Data Science projects that will be of interest to you. If you select a dataset, please include the competition details)
    • https://www.datasciencecentral.com/profiles/blogs/the-free-big-data-sourceseveryone-should-know
  • Describe the dataset you selected and provide details on what you will do with it. Make sure you
    • select a dataset that will be available to you over the next 2 months.
  • (if possible at this time) Describe possible hypotheses regarding the data. (This is optional at this
    • stage of the project).
  • Describe the analytic tools you would like to use for exploring the data.
  • Your submission should be no more than one page.
  • Only one team member should submit your project proposal
    • Two key project deliverables:
  • Presentation of the Project
  • Term Paper:
    • Option I-Paper according to template of CFP as agreed upon with instructor.
    • Option II-
      • Introduction
      • Problem Statement
      • Description of Dataset
      • Description of model/algorithm used
      • Description of tools used at all stages of the Data Analytics Lifecycle
      • Analysis and Discussion
      • Conclusion

Prof. Angela

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