Free Practice Questions for Snowflake GES-C02 Certification

Subdomain 1.1: Define AI & ML fundamentals

• Define key AI and ML concepts
• Supervised learning
• Unsupervised learning
• Reinforcement learning
• Generative AI
• Discriminative AI
• Common AI tasks

Subdomain 1.2: Describe AI lifecycle and MLOps

• Outline AI lifecycle stages
• Data preparation
• Model training
• Evaluation
• Deployment
• Monitoring
• MLOps principles and practices

Subdomain 1.3: Understand AI ethics and responsible AI

• Discuss ethical considerations in AI
• Bias
• Fairness
• Transparency
• Accountability
• Mitigating bias in AI models
• Explainability and interpretability

Subdomain 2.1: Utilize Snowflake Cortex AI

• Describe Snowflake Cortex AI capabilities
• Building and deploying AI models
• Forecasting
• Anomaly detection
• Classification

Subdomain 2.2: Apply Snowflake Intelligence

• Define Snowflake Intelligence
• AI-driven insights
• Natural language querying
• Automated insights
• Integration of Snowflake Intelligence

Subdomain 2.3: Implement Cortex Code and MCP

• Cortex Code for AI application development
• Model Context Protocol (MCP)
• Connecting AI models to data sources

Subdomain 2.4: Leverage AI functions (AI_TRANSCRIBE, AI_REDACT, AI_FILTER)

• Use cases for AI_TRANSCRIBE
• Use cases for AI_REDACT
• Use cases for AI_FILTER
• Applying AI functions to process and transform data
• Syntax and parameters for AI functions

Subdomain 3.1: Prepare data for AI workloads

• Data preparation steps
• Cleaning
• Normalization
• Feature engineering
• Handling missing data
• Handling outliers
• Data transformation

Subdomain 3.2: Manage data pipelines for AI

• Design and implement data pipelines
• AI model training and inference
• Snowpipe
• Tasks
• Streams
• Continuous data loading
• Data versioning

Subdomain 3.3: Ensure data quality and governance

• Data quality metrics
• Validation techniques for AI datasets
• Data governance frameworks
• Snowflake features for data masking
• Snowflake features for tagging

Subdomain 4.1: Deploy AI models in Snowflake

• Deploying AI models within Snowflake
• External functions
• Snowpark
• Registering models in Snowflake
• Invoking models in Snowflake

Subdomain 4.2: Integrate AI with applications

• Integrating AI models with applications
• APIs
• Connectors
• Snowflake drivers
• SDKs
• Real-time integration
• Batch integration

Subdomain 5.1: Secure AI data and models

• Security best practices for AI data and models
• Encryption
• Access controls
• Network policies for AI workloads
• Compliance requirements for AI data handling

Subdomain 5.2: Monitor and govern AI models

• Monitoring AI model performance
• Monitoring model drift
• Governance processes for model approval
• Auditing
• Documentation
• Snowflake features for tracking