Skill Course
LLM, Multimodal & Generative AI Foundations
Understand and integrate the model capabilities behind modern generative AI products.
Learning objectives
Explain key LLM and multimodal concepts
Select models based on capability, cost and latency
Integrate text and multimodal model APIs
Generate validated structured outputs
Recognize model risks and responsible-use constraints
Course coverage
Generative AI, foundation models, LLMs, transformers and inference fundamentals
Tokens, embeddings, context windows, sampling, temperature and model behavior
Major AI providers and APIs: OpenAI, Anthropic, Gemini, Bedrock and open-source models
Chat and completion APIs, streaming, structured outputs and function/tool calling
Embeddings, semantic similarity and vector-representation fundamentals
Multimodal AI: text, vision, audio, speech and document understanding
Model selection, capabilities, limitations, hallucinations and reliability
Token usage, latency, model pricing, cost and provider tradeoffs
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