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The course starts with how a prompt is built, covering instructions, context, input data and output indicators, before moving to LLM settings and formatting. That order is useful: it gives you a checklist for debugging weak prompts instead of rewriting them at random.
Zero-shot, few-shot and Chain of Thought prompting are the named methods in the description. The skills list adds RAG, LangChain and AI workflows, so the material appears to extend past single prompts into systems that feed models data.
The title says advanced but the listed level is beginner. Learners with no background should expect new terms to arrive quickly, while experienced prompt writers may find the opening sections a review. Either way, the emphasis on structure and output control is the part worth keeping.
Skills you'll gain: LangChain, Retrieval-Augmented Generation, Generative AI, AI Workflows, LLM Application, Large Language Modeling, Data Synthesis.
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