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Build data pipelines in Snowflake: ingest data at scale, transform it with SQL and Python, orchestrate workflows, and apply DevOps and observability practices.
Build production-ready AI agents with Snowflake Cortex: configure semantic views for natural language database queries, create hybrid search over unstructured text, and integrate agents via Model Context Protocol.
Create Snowflake virtual warehouses, stages, and databases, use time travel and cloning, write UDFs and stored procedures, and explore Snowpipe, Cortex LLM, and Streamlit workloads.
Build continuous data pipelines in Snowflake: ingest with COPY INTO and connectors, transform using SQL and Snowpark, deliver via Marketplace and Streamlit, orchestrate with tasks and DAGs.
Build generative AI applications on Snowflake: use Cortex LLM functions for summarization, translation and sentiment analysis, engineer prompts, and fine-tune Mistral-7b with Streamlit front ends.
Apply DevOps to Snowflake data pipelines: add git source control, deploy with GitHub Actions and Snowflake CLI, and monitor health using event tables, logs, traces, and alerts.
Build conversational apps over your own data: RAG on documents with Cortex Search, text-to-SQL with Cortex Analyst, and Streamlit frontends deployed end to end.
Turn a few lines of Python into a shareable GenAI web app: build a Streamlit chatbot, add Snowflake Cortex and RAG, then deploy it.
Build a multi-agent data agent in LangGraph that plans, searches the web and Snowflake Cortex, then trace and evaluate it with LLM-as-a-judge and GPA metrics.
Build autonomous agents on Snowflake Cortex: create semantic views for Cortex Analyst, configure Cortex Search, write orchestration instructions, evaluate reliability, and connect via Model Context Protocol.
Build AI-powered pipelines that turn images, audio, and video into LLM-ready text: apply OCR and ASR, prompt Vision Language Models, and implement multimodal RAG over meeting recordings.
Build an Apache Iceberg lakehouse with catalogs, Spark and Trino: design hidden partitioning, migrate Hive and Parquet data, and run compaction, branching and snapshot expiration.
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