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Duration 14 hours
Course Outline
Introduction to Ollama in Finance
- Understanding local LLM deployment
- Advantages of on-device AI in the financial sector
- Primary features and constraints of Ollama
Configuring Ollama for Financial Settings
- System preparation and model installation
- Configuration methods for financial tasks
- Maintaining secure operational environments
Primary Financial Use Cases
- Automating financial reporting
- Assisting with risk assessment and analysis
- Summarising markets and deriving insights
Customising and Fine-Tuning Models
- Engineering prompts for financial scenarios
- Enhancing models with domain-specific data
- Striking a balance between accuracy and performance
System Integration and Automation
- Establishing API connections and workflows
- Integrating with financial systems and tools
- Scripting for automated financial processes
Governance, Security, and Compliance
- Safeguarding data confidentiality
- Ensuring adherence to financial regulations
- Best practices for secure deployment
Model Evaluation and Validation
- Techniques for measuring accuracy
- Workflows for risk mitigation and validation
- Continuous improvement of models
Operational Deployment and Support
- Strategies for monitoring and optimisation
- Version control and model updates
- Resolving common technical challenges
Summary and Next Steps
Requirements
- A solid grasp of financial workflows
- Practical experience with data analytics or financial systems
- Familiarity with fundamental AI and machine learning principles
Target Audience
- Finance professionals
- Financial IT teams
- Analysts and technical administrators
Testimonials (1)
i already have some reports that i know, i will use some of the prompts that looked at today
