Foundation Models, LLMs & Multimodal AI
AIDU-FM-103
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.