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Applied Artificial Intelligence

CISC 339
Fermé
Contact principal
Mercy University
Mercy University
Dobbs Ferry, New York, United States
Tianyu Wang
Assistant Professor
(1)
4
Chronologie
  • janvier 24, 2024
    Début de expérience
  • mai 14, 2024
    Fin de expérience
Expérience
1 projets souhaités
Dates fixées par le expérience
Entreprises privilégiées
N'importe où
Tout type de entreprise
N'importe qu'elle industrie

Portée de Expérience

Catégories
Technologie de l'information Apprentissage automatique Intelligence artificielle
Compétences
searching algorithms logic deduction problem solving supervised learning neural networks optimization algorithms
Objectifs et capacités de apprenant.es

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.


Apprenant.es

Apprenant.es
Premier cycle universitaire
Tout niveau
25 apprenant.es dans le programme
Projet
30 heures par apprenant.e
Les Professeur.euses affectent les apprenant.es à des projets
Équipes de 3
Résultats et livrables attendus

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


Chronologie du projet
  • janvier 24, 2024
    Début de expérience
  • mai 14, 2024
    Fin de expérience

Exemples de projets

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.)

Critères supplé mentaires pour entreprise

Les entreprises doivent répondre aux questions suivantes pour soumettre une demande de jumelage pour cette expérience:

  • Q1 - Texte court
    Provide relevant information/data as needed for the project.  *
  • Q2 - Texte court
    How is your project relevant to the course?  *
  • Q3 - Texte court
    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 - Texte court
    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 - Texte court
    Provide an opportunity for students to present their work and receive feedback.  *