Knowing good and bad of a professor is very important for college students when deciding which course to take. However, looking through the Internet and reading comments and rating from various websites and other students are time consuming. So we decided to use Alexa to help us look through the information from the Internet.

What it does

Rating Professor helps user looking up professor information on the Internet, then generating rating of the professor and read comments of that professor from students.

How we built it

We use the concept of Finite State Machine.


Accomplishments that we're proud of

  • Built Professor Rating Alexa Conversation to help students query professor rating without hand.
  • We provided excellent user experience, by providing Professor Rating with multiple outputs in every scenes.
  • Comparing to the pizza example, we use Finite State Machine to simplify the process, and make the architecture of our program more clear.

What we learned

  • How to use Typescript and Amazon Lambda to deploy an API.
  • How to use Python to fetch and clean Professor Rating data.
  • How to use GraphQL to query fast and easy.
  • How to use Finite Auto Machine in real life.

What's next for Professor Rating

Improve User Experience

  • Adding more human like responds, more clearly data.
  • Adding composite input ability (ex. when user say "select {professor} in {school}", we will automatic parse these parameters).
  • Improving Professor Selection Accuracy.

Open Source

  • Let others help us to improve experience and fix bugs.
  • Providing API to query Professor Rating in any platform, anytime, anywhere.
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