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***Module 1: Advanced Prompt Engineering for Text-to-SQL.** Use Amazon Bedrock to implement some of the State-of-the-Art techniques against an Amazon Athena data set and a relational database.
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***Module 2: Retrieval Augmented Generation (RAG) for Text-to-SQL.** Leverage a FAISS in-memory vector store of data set meta data to improve query accuracy.
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***Module 3: Fine-tuning for Text-to-SQL.** Fine-tune a Titan model on the Spider Dataset to improve Text-to-SQL accuracy.
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***Module 4: Introduction to Security for Text-to-SQL.** Guard against prompt injection and SQL injection using these prompt engineering techniques.
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