AI Model Selection and Training

AI Model Selection and Training is a half-day course that introduces a practical tools for evaluating and choosing the right AI models across traditional machine learning and modern generative AI systems. Participants learn to understand key trade-offs, and address issues such as concept drift and hallucination. The session also provides an overview of advanced techniques like retrieval-augmented generation (RAG), Model Context Protocol (MCP) and parameter-efficient fine-tuning (PEFT), giving attendees the insight needed to begin their journey in this rapidly evolving space.

Topics Discussed:

1. Role of Model Selection
2. Traditional ML vs. Deep Learning vs. Generative AI Approaches
3. Model Selection Criteria
4. Tradeoffs
5. LLM Attributes and Tradeoffs
6. Open-Source vs. Proprietary

This course is included in the AI Learning Subscription.

Duration

½ day

Audience

AI Developers, Data Science Personnel, Architects, SREs, AIOps, PlatformOps and DevOps personnel.

Register 21 days before class start date and save 10%! Enter discount code EARLY10 during registration.

Register 21 days before class start date and save $250! Enter discount code EARLY250 during registration.

Is there a discount available for current students?

UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.

What is the cancellation and refund policy?

Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.