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Course Outline
Introduction to WrenAI OSS
- Overview of WrenAI architecture
- Key OSS components and ecosystem
- Installation and setup
Semantic Modeling in Wren AI
- Defining semantic layers
- Designing reusable metrics and dimensions
- Best practices for consistency and maintainability
Text to SQL in Practice
- Mapping natural language to queries
- Improving SQL generation accuracy
- Common challenges and troubleshooting
Prompt Tuning and Optimization
- Prompt engineering strategies
- Fine-tuning for enterprise datasets
- Balancing accuracy and performance
Implementing Guardrails
- Preventing unsafe or costly queries
- Validation and approval mechanisms
- Governance and compliance considerations
Integrating WrenAI into Data Workflows
- Embedding Wren AI in pipelines
- Connecting to BI and visualization tools
- Multi-user and enterprise deployments
Advanced Use Cases and Extensions
- Custom plugins and API integrations
- Extending WrenAI with ML models
- Scaling for large datasets
Summary and Next Steps
Requirements
- Strong understanding of SQL and database systems
- Experience with data modeling and semantic layers
- Familiarity with machine learning or natural language processing concepts
Audience
- Data engineers
- Analytics engineers
- ML engineers
21 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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