Note: This project template serves as a guiding framework to help generate ideas when creating a project for the Polygence Intership program. It is flexible and can be adapted to fit your organization’s specific needs.

Our company advertises thousands of products, and we want to leverage the latest technology to gain market advantage. Applications of this technology include recommendation algorithms, predictive analytics like lifetime values, fraud detections, and classifications. We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to our existing dataset. Students will develop an AI / ML model related to any of the aforementioned applications.

This will involve several different steps for the students, including:

• Conducting background research on our existing products and the dataset.
• Analyzing our current dataset.
• Researching the latest AI / ML techniques and how they could be applied to our data.
• Developing an AI / ML model that provides unique outcomes or insights into our data.
• Providing multiple solutions that can be applied to solve the same problem.

The project outcomes should align with beginner level capability. Polygence Internship students are new to or are acquiring foundational skills in the subject area of the project. The deliverables are noted with a 4 week window as the foundation. You will be assigned a team of 2-3 students for your project and the outcomes/deliverables should be achievable within 40-60 hours per student over a 6 week period.

By the end of the project, examples of outcomes are:

• Understanding of the available dataset
• Understanding of the latest AI / ML techniques
• Identification of ways in which AI / ML can be applied to our company

Final deliverables should include

• A final report on the dataset, the problem solved, methodologies and approaches, outcomes and results, and recommended next steps.

How will you support learners in completing the project?

Students will connect directly with us for mentorship throughout the project. We will be able to provide answers to questions such as:

• Our current products and applications of AI / ML
• The current data set and guidance in navigating it
• Current industry standard approaches to AI / ML
• Input on choices, problems or anything else the students might encounter.