Essentials of Large Language Models: A Beginner’s Journey

An understanding of language models and large language models, including their capabilities, applications, and limitations

Familiarity with the inference journey of an LLM, including tokenization, embeddings, positional encodings, and attention mechanisms

Working knowledge of how LLMs are trained for next-token prediction, including pretraining at scale and assistant alignment concepts

Working knowledge of the developer toolkit for building with LLMs, including prompting, embeddings for semantic search, RAG, and tools/function calling

Hands-on experience choosing when to prompt, use RAG, or fine-tune, and evaluating outputs with basic guardrails for production use