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Artificial Intelligence Advanced Certificate

Artificial Intelligence Advanced Certificate

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New York State Approved Advanced Certificate Program in Artificial Intelligence
(F-1 students are not eligible for Advanced Certificate programs)

Program Overview – Advanced Certificate in Artificial Intelligence

  • Designed to provide a strong foundation in Artificial Intelligence and Machine Learning
  • No master’s degree required for admission
  • Ideal for:
    • Career changers
    • Professionals looking to upskill with an advanced credential
    • Individuals pursuing AI-related certifications
  • 3-course program offering targeted, high-impact learning
  • Students earn a micro-badge upon completion
  • Courses selected to ensure a well-rounded AI education
  • Prepares students for professional certifications in AI and Machine Learning

Mode of Delivery for AI Courses

  • Delivered via Canvas Learning Management System (LMS).
  • Structured into learning modules:
    • Assigned readings
    • Recorded video lectures or narrated slides
    • Discussion boards and peer interaction
    • Assignments, quizzes, or projects
  • Flexible log-in schedule to accommodate work and life balance.
  • Expectations and due dates clearly outlined in both the syllabus and module.

Artificial Intelligence Advanced Certificate Courses

MAIN 610

AI Principles and Practice
This course explores the fundamentals of Artificial Intelligence (AI), emphasizing ethical considerations and practical application. Students will explore foundational AI concepts—including machine learning, natural language processing, and intelligent systems—while examining their implications across industries such as healthcare, finance, education, and government. No technical background is required; the course is designed to build practical fluency in AI concepts and decision-making for professionals across domains.
3 Credits

MAIN 620

The Practice of Generative AI
This course focuses on the practical implementation of generative artificial intelligence, emphasizing the operational skills required to leverage these tools effectively in professional settings. Students will develop expertise in prompt engineering and retrieval augmented generation (RAG), learn frameworks for evaluating the performance and reliability of generative AI outputs, learn how fine-tuning can be used to improve performance for specific applications, and explore best practices for integrating generative models into existing workflows and systems.
3 Credits

MAIN 625

AI System Design
Students learn how to design systems and processes that use AI as a key component. This course emphasizes the design, implementation, and management of AI-driven processes across various applications, including autonomous systems, predictive analytics, and intelligent interfaces. Students will learn how to practically use a variety of AI techniques including reinforcement learning, fine-tuning, retrieval-augmented generation (RAG), and predictive modeling, and how to embed them in effective software systems. They will explore application in fields such as healthcare, customer service, marketing, autonomous vehicles, smart cities, and environmental monitoring, among others, with a focus on real-world applications. Learning is through case studies and practical exercises.
Prerequisite: MAIN 620 or MAIN 622
3 Credits