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Foundation Models, LLMs & Multimodal AI
Course

Foundation Models, LLMs & Multimodal AI

AIDU-FM-103

Duration
1 Day
Format
Virtual or in-person
Intermediate LevelNon-Technical AudienceAI AdoptionAI Failure Modes & LimitsLarge Language Models

About this course

This course provides a clear, non-technical understanding of foundation models, large language models, and multimodal AI for professionals who evaluate, govern, or deploy these systems in real organizational settings.

Participants learn how foundation models differ from traditional machine learning, how large language models generate fluent outputs without understanding meaning, and how multimodal systems combine text, images, audio, and other signals. The course focuses on real-world behavior, limitations, and failure modes, including hallucinations, prompt sensitivity, over-generalization, and misuse risks.

Rather than teaching tools or prompting tricks, the course builds durable mental models that explain why these systems work, why they fail, and how naive adoption creates operational, legal, and reputational risk. Participants connect model behavior to governance, accountability, and safety, enabling informed decisions about where these systems add value and where they should not be relied upon.

Course topics

What you'll be able to do

Explain what foundation models are and how they differ from traditional ML systems
Understand how large language models generate text without understanding meaning or truth
Describe how multimodal models integrate text, images, audio, and other signals
Recognize why fluent outputs are not evidence of correctness or reasoning
Identify common failure modes, including hallucinations, prompt instability, and over-generalization
Distinguish prompting, fine-tuning, and system-level controls, and understand their tradeoffs
Evaluate risks related to safety, compliance, data leakage, and misuse
Determine appropriate organizational boundaries for deploying foundation models
Critically assess vendor claims, demos, and benchmarks involving LLMs and multimodal AI