Udemy - Certification Course Snowflake SNOWPROⓇ SPECIALTY - GEN AI torrent

Certification Course Snowflake SNOWPROⓇ SPECIALTY : GEN AI

https://WebToolTip.com

Published 10/2025
Created by HadoopExam Learning Resources
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 110 Lectures ( 7h 35m ) | Size: 2.42 GB

Master Snowflake Gen AI Fundamentals for the SnowPro Specialty Exam — Concept-Driven Prep

What you'll learn
Master Snowflake Cortex AI fundamentals—LLMs, Cortex Search, Cortex Analyst, Fine-tuning, and Snowflake Copilot—to solve real enterprise Gen AI use cases.
Implement Retrieval-Augmented Generation (RAG) in Snowflake using vector embeddings, semantic search, and Cortex Search indexes for high-quality answers.
Use Snowflake LLM functions (COMPLETE, TRY_COMPLETE, SUMMARIZE, TRANSLATE, CLASSIFY_TEXT, EXTRACT_ANSWER, PARSE_DOCUMENT, EMBED_TEXT_768/1024) with SQL and REST
Build text-to-SQL analytics with Cortex Analyst, including semantic model creation (YAML/semantic views), Suggested Questions, and Verified Query Repository (VQ
Evaluate model choices for capability, latency, and cost; apply COUNT_TOKENS and token-minimization patterns for predictable spending.
Fine-tune LLMs in Snowflake (Cortex Fine-tuning) and register open-source models via Snowflake Model Registry and Snowpark Container Services.
Design multi-turn chat applications on Snowflake data (e.g., Streamlit) with robust session state, parameter control, and secure invocation of Cortex functions.
Productionize AI pipelines: enrich, transform, and extract insights from unstructured text (transcripts, PDFs) using COMPLETE Structured Outputs and SQL tasks.
Enforce Gen AI governance with RBAC, guardrails, model allow-lists (CORTEX_MODELS_ALLOWLIST), and secure REST authentication strategies.
Monitor and optimize costs using Snowflake service consumption tables, CORTEX_FUNCTIONS_USAGE_HISTORY, and Cortex Search/Analyst usage views.
Apply AI observability (traces, evaluations, comparisons, event tables) and TruLens-based metrics to improve quality and reduce hallucinations.
Configure cross-region inference (CORTEX_ENABLED_CROSS_REGION) and architect for availability, latency, and data residency requirements.
Operationalize Document AI: prepare documents, train models, use !PREDICT, automate pipelines, and troubleshoot errors and limits.
Meet exam scenarios with hands-on patterns for RBAC, guardrails, bias mitigation, error handling, and secure data access across SQL and Python.
Confidently map SnowPro Specialty: Gen AI exam domains (Overview, LLM Functions, Governance, Document AI) to real-world tasks and best practices.

Requirements
No prior Snowflake or Gen AI experience required—this course starts from first principles and builds up to exam-ready skills.
A free Snowflake trial account (or company account) and a modern web browser are sufficient for hands-on practice.
Basic SQL or Python is helpful but not mandatory; all labs include step-by-step walkthroughs and copy-paste code.
Works on Windows, macOS, or Linux—no special hardware or paid tools needed beyond internet access.
Curiosity and a willingness to learn are the only requirements; the course provides templates, cheat sheets, and guided exercises.