University College of the North
University College of the North
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Applied Artificial Intelligence

CISC 339
Closed
Mercy University
Mercy University
Dobbs Ferry, New York, United States
Tianyu Wang
Assistant Professor
4
Timeline
  • January 24, 2024
    Experience start
  • May 14, 2024
    Experience end
Experience
1 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries

Experience scope

Categories
Information technology Machine learning Artificial intelligence
Skills
searching algorithms logic deduction problem solving supervised learning neural networks optimization algorithms
Student goals and capabilities

Looking to elevate your organization, and bring it to the next level? Bring on learners from Mercy University to be your learner-consultants, in a project-based experience. Learners will work on one main project over the experience of the semester, connecting with you as needed with virtual communication tools.


The purpose of this project is to provide students with an opportunity to apply existing AI and Machine Learning algorithms to wide application area. In the lecture, students are introduced to the use of classical artificial intelligence techniques and machine learning algorithms, which they would be able to apply to a project in your organization.


Students

Students
Undergraduate
Any level
25 students
Project
30 hours per student
Educators assign students to projects
Teams of 3
Expected outcomes and deliverables

Deliverables will vary depending on the scope of the internship. However, these deliverables must be discussed and agreed upon prior to the start of the internship.


Some final project deliverables might include: 

  1. A 10-15 minute presentation on key findings and recommendations
  2. A detailed report including their research, analysis, insights and recommendations


Project timeline
  • January 24, 2024
    Experience start
  • May 14, 2024
    Experience end

Project Examples

Requirements

Learners can complete a substantial project for your organization over the placement period. We suggest providing a starting project, but as the placement goes on there may be other duties or projects the learner is asked to complete as well. Providing a central project creates structure for the internship, and gives the learner (and company) a tangible goal.


Project activities that learners can complete may include, but are not limited to: 

  • Implementation of widely used AI algorithms in Python
  • Search algorithms: uninformed and informed search, constraint satisfaction
  • Probabilistic models and logical reasoning under uncertainty
  • Use various machine learning techniques like regression, decision trees, and SVM.
  • Apply algorithms to find solutions in different environments (maze, inference, climb-hill, linear programming, CSP problem, etc.)

Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

  • Q1 - Text short
    Provide relevant information/data as needed for the project.  *
  • Q2 - Text short
    How is your project relevant to the course?  *
  • Q3 - Text short
    Be available for a quick phone/virtual call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the experience.  *
  • Q4 - Text short
    Provide a dedicated contact person who is available for weekly/bi-weekly drop-ins to address students’ questions as well as periodic messages over the duration of the project.  *
  • Q5 - Text short
    Provide an opportunity for students to present their work and receive feedback.  *