UK has a summer program, the NACME Google Applied Machine Learning Intensive (AMLI) for undergraduates who are URM. The program is an all expense paid, 8-week summer program. Undergraduates, Graduate Students, and Faculty should apply here: https://amli.engr.uky.edu
Undergraduate students receive the following
- 20 current students will be selected to participate in the rigorous and exciting learning environment over the course of 8 weeks.
- Receive full room and board during the 8 week program. Students will stay in the Ball Hall dorms.
- Receive travel stipend to cover the arrival and departure costs.
- Potentially receive a stipend for participating in the program (pending).
- Earn upper-division CS elective course credit for completing the bootcamp. Students will be able to transfer this credit into their respective university/department, pending their respective university policies and guidelines.
Graduate students receive the following
- A competitive salary, $8k – $12k for teaching during the 8 week bootcamp.
- Travel stipend to cover the arrival and departure costs to Lexington, KY.
- Interact with other graduate student researchers and faculty.
- Graduate student teachers are required to relocate to Lexington, KY during 8 weeks of the AMLI program.
- Learn the curriculum before your arrival. If selected, the curriculum will be provided to you.
- Teach and interact with the AMLI students for 2-3 hours a day, 5 days a week.
- Utilize 5-6 hours of the day to collaborate on research with the Network Reconnaissance Lab or other labs at UK.
Faculty are encouraged
- Submit a 2 page project proposal related to ML. If your project is selected, 2-4 of the AMLI students will be assigned to your project during the last 4-5 weeks of the program. The students will apply their new found ML skills to your proposed project.
- Faculty leading a project will mentor students as well as have them interact with their research lab.
- Faculty are encouraged to apply for NSF REU funds to support stipends for the students on their project.