Your final project this semester will be a large program that deals in some way, shape, or form with Data Science. This is your chance to use Python to perform a task that YOU are interested in and use it to do Data Science.

You will create a proposal to be handed in via the Canvas no later than July 23nd (If this is a day or two late it’s no issue). You should treat this assignment as if you are pitching a product or an advertising campaign. Think Shark Tank (I am your investor, investing grades; sell me on your A). Act as if you are presenting the idea for your program’s service to a venture capitalist. Nothing technical need be discussed for the pitch/proposal, just an idea and the problem your code is going to solve. Do not tell me about data types and sources, this is a pitch, big picture! The presentation can be a powerpoint, a written document, a video, whatever. Have fun with it.

Then, on July 29th, you will submit your demonstration presentation (same as the proposal, slides, video, have fun) and your project code in Canvas.

The deliverables for this assignment are as follows:

1. Proposal – Due July 23nd

2. Demo (video,slides,etc.) – Due July 29th

3. Code – Due July 29th

I am not expecting one million lines of code. If you can accomplish a serious Data Science task without a boatload of code I’m fine with it, but I want you to use what you’ve learned in order to perform a real world useful task. That’s all. Don’t sweat the small stuff, think big and have fun.

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The Code Rubric (What I expect to see in the code at the end of the day)

I would like to see certain things that reflect what you have learned over this semester in your project.

· A custom library (with classes, functions, and constants)

· Iteration and decision making

· imports from your library and the standard library

· If you import a third party library, report it ahead of time. I want to be able to run your code on my computer so if you use 20 third party libraries I’m going to be unhappy about it.

· File I/O – you must read input from a file and produce an output file.

· The use of a data structure (you will understand this soon, Unit 6)

· The use of object orientation (you will understand this soon as well, Unit 5). Specifically, I would like to see inheritance.

The Data

· You must use a data file with over 10,000 items. They do not have to be random. They can be programmatically formed (we do not expect you to handwrite thousands of lines of data). They can be sorted or unsorted as you desire (sorting may be useful, but that depends on what you’re doing; it’s up to you).

· Items means records. You cannot have 100 lines of 1,000 data points. I’m looking for 10K unique records.