MET CS 677 Project Guidelines
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MET CS 677 Project Guidelines (Online Class)
One of the requirements for MET CS 677 is the final project (15% of the grade). The project must be done individually. This is an opportunity for you to be creative in solving a data science problem that is of interest to you. The project should be challenging enough so that you could discuss it at future interviews with potential employers. Your project will also give us an opportunity to provide you with a future reference if you ever need it.
For the online class, you will have to record your (3-to-5 minutes) presentation of your results using Kaltura video (similar to youtube). Then share the project presentation video at the “Media Gallery” section.
How to record a video and share at the “Media Gallery” section?
• Check out the direction touse Kaltura to capture and post or submit video.
• Inside the Kaltura direction, under the section of “Posting or Submitting Your Video in Your Course”, follow the steps under “B. For sharing a video in the Media Gallery area”.
In addition to presentations, you will submit the following:
1. one-to-two-page summary of what you have done and what were the main results
2. source file(s)
3. instructions how to run your code
Some of you are doing projects related to your work and we may not be able to run your code. In this case, send us examples of runs with your summary. The presentations should be at the level that other students can understand what your project is all about. Imagine that you have an interview and you are asked to describe in a few words a data science project of your choice.
You are free to choose any topic that is of interest to you. The most important thing to keep in mind that this is a data science/machine learning project in Python. You will not be judged on the originality of your topic or the difficulty of implementation. We want you show us that you can analyze a data science problem and write a short summary of your results.
You are also free to pick up a data science/machine learning method or use any additional library that was not covered or used in class (e.g. deep learning or recommendation systems).
In short, this is an opportunity for you to explore data science and do something that is of interest to you. We are asking you to send us your 1-2 sentence proposals so that we could assess if your project may be too difficult.
Finally, your project should contain no confidential data from your employer or any non-public data source.
Good luck to all of you.
2021-12-04