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Student Class Predictor

Many schools and universities are challenged to not only pick classes that students will attend, they have challenges understanding the staging of classes and the hiring of the resources for teaching the class. This AI will be an ongoing monitoring tool that can help predict the type of classes that should be provided, how many people will be in the classes and the number of professors needed to support the class.

User Stories

Overall Product Model

  • Demand: Universities by their nature have always struggled to meet the demands of the market and organizations that rely on their development of the next generation, to meet the demands of the professors whom are focused on research and teaching that is in alignment with their specialties and finally in alignment with the students who seek to find a profession that will truly add value to society and their own lives.

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  • Inputs: Historical Records of previous classes, job postings, current and past profiles of students and teaching staff. Future guidance in areas that the University thinks will be a focus for that administration.

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  • Outputs: Detailed recommendations on classes to provide, class size structure and locations, and recommended required number of teaching/professor staff.

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  • Model Testing: In building the model, we would just leave out sections of the data that historically we know of in the past and then input the data to see if the AI BOT will predict to the real results.

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  • Compliance: Compliance measures would be a battery of historical data that would be fed into the AI and an expected range for results would be monitored. If the AI Bot is outside of this standard, the AI BOT will need to be evaluated and retrained or adjusted to come into compliance.

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  • Market Value: Univerisites will need this type of tool to remain relevant in the market place in providing the best experience for students and professors where their knowledgeable and meaningful to the market place. This product would most likely be a on premises solution that would be paid by calculation points, # Classes to assess, # of Students to review and general # of Teaching positions. Depending on this mix there would be monthly or yearly fees. Value should be significant by department.

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