Overview

This two‐day course provides a practitioner‐level introduction to the Snowflake AI Data Cloud. Designed for professionals who will actively work on the platform, the course follows a persona‐driven approach where Data Analysts, Data Engineers, and Platform Administrators learn together through shared lectures, then apply concepts through role‐specific hands‐on labs in Snowflake Workspace Notebooks.

The course employs a repeatable instructional cadence — Lecture, Practice Lab, Huddle — across all mod‐ ules. Cortex Code (CoCo) is integrated as a learning tool throughout, enabling students to focus on work‐ flows and problem‐solving rather than syntax memorization.

This course serves as the recommended prerequisite for all specialty courses including Data Engineering, Data Analyst, Administering Snowflake, GenAI, and Security.

Skills Covered

  • Navigate the Snowflake AI Data Cloud interface and object hierarchy using Snowsight and Workspaces.
  • Use Cortex Code (CoCo) as an AI‐powered assistant for querying, debugging, and workflow generation.
  • Configure role‐based access control (RBAC) and understand Snowflake’s security model.
  • Monitor and manage compute credits and cost using Account Usage views and resource monitors.
  • Apply Cortex AI functions (sentiment, classify, extract, summarize) to structured and unstructured data.
  • Discover and mount datasets from the Snowflake Marketplace.
  • Load and transform data using stages, file formats, and COPY INTO.
  • Employ Continuous Data Protection features including Time Travel and cloning.
  • Process unstructured documents using AI_PARSE_DOCUMENT and Cortex Search.
  • Complete a capstone project integrating multiple skills in a real‐world scenario

Prerequisites

  • Completion of Snowflake Platform Training (SPT) or equivalent awareness‐level familiarity with Snowflake.
  • Recommended completion of the free on‐demand “Snowflake Multi‐Factor Authentication (MFA) Essentials” course.
  • Basic SQL knowledge is assumed

Target Audience

This course is designed for three practitioner personas who will actively work on the Snowflake platform:

  • Data Analysts — querying, reporting, visualizations, and AI‐powered analysis
  • Data Engineers — pipelines, loading, transformation, and orchestration
  • Platform Administrators — security, roles, cost management, governance, and monitoring

Course Curriculum

Module 1: Orientation & Architecture

  • Snowflake AI Data Cloud overview and structure
  • Storage, Compute, and Cloud Services layers
  • Navigating Snowsight and Workspaces
  • Object hierarchy: databases, schemas, tables, views
  • Lab: Navigate objects, explore the shared dataset, create personal workspace

Module 2: Querying with Cortex Code (CoCo)

  • Introduction to CoCo as an AI coding assistant
  • Natural language to SQL generation
  • Iterative query refinement and debugging
  • Lab: Query the course dataset using CoCo, build persona‐relevant reports

Module 3: Access Control & RBAC

  • Roles, privileges, and the grant hierarchy
  • Ownership and discretionary access control
  • Principle of least privilege
  • Lab: Configure grants, demonstrate deny→grant flow, persona‐specific access scenarios

Module 4: Credits & Cost Management

  • Compute credit model and pricing
  • Warehouse sizing, scaling, and auto‐suspend
  • Account Usage views for cost monitoring
  • Resource monitors and alerts
  • Lab: Analyze warehouse usage, right‐size a warehouse, explore cost attribution

Module 5: Cortex AI Functions

  • AI_SENTIMENT, AI_CLASSIFY, AI_EXTRACT, AI_SUMMARIZE
  • AI_COMPLETE for custom prompts
  • Applying AI functions to business data
  • Lab: Apply AI functions to course dataset per persona use case

Module 6: Data Landscape & Marketplace

  • Snowflake Marketplace overview
  • Discovering and mounting shared datasets
  • Data sharing concepts
  • Lab: Browse Marketplace, mount a dataset, query third‐party data

Module 7: Getting Data In

  • Stages (internal and external)
  • File formats and COPY INTO
  • Transformations during load
  • Lab: Load CSV/JSON data, apply transformations, validate results

Module 8: Time Travel & Data Protection

  • Continuous Data Protection (CDP) overview
  • Time Travel: querying historical data, UNDROP
  • Zero‐copy cloning
  • Lab: Recover dropped/modified data, create clones, explore retention

Module 9: Unstructured Data & AI

  • Working with files on stages
  • AI_PARSE_DOCUMENT for text extraction/OCR
  • Cortex Search for semantic retrieval
  • Lab: Process documents from stage, extract structured fields, build a search index

Module 10: Capstone Project

  • Integrative project combining multiple modules
  • Persona‐driven scenario: solve a real‐world problem end‐to‐end
  • Instructor‐facilitated final huddle and reflection

Dates & Locations

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October 27, 2026 - October 28, 2026

Location: Online
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November 5, 2026 - November 6, 2026

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December 8, 2026 - December 9, 2026

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