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Course Outline
Introduction to Ollama in Finance
- Understanding local LLM deployment
- Benefits of on-device AI in finance
- Key capabilities and limitations of Ollama
Setting Up Ollama for Financial Environments
- System setup and model installation
- Configuration techniques for financial tasks
- Managing secure environments
Core Finance Use Cases
- Automated financial reporting
- Risk assessment and analysis assistance
- Market summarization and insights
Customizing and Fine-Tuning Models
- Prompt engineering for finance scenarios
- Domain-specific data enhancement
- Balancing accuracy and performance
System Integration and Automation
- API connections and workflows
- Integration with financial systems and tools
- Scripting for automated financial processes
Governance, Security, and Compliance
- Ensuring data confidentiality
- Compliance with financial regulations
- Best practices for secure deployment
Model Evaluation and Validation
- Accuracy measurement techniques
- Risk mitigation and validation workflows
- Continuous model improvement
Operational Deployment and Support
- Monitoring and optimization strategies
- Versioning and updating models
- Resolving common technical issues
Summary and Next Steps
Requirements
- An understanding of financial workflows
- Experience with data analysis or financial systems
- Familiarity with basic AI or machine learning concepts
Audience
- Finance professionals
- Financial IT teams
- Analysts and technical administrators
14 Hours
Testimonials (3)
Trainers can answer all questions and accept any queries
Dewi Anggryni - PT Dentsu International Indonesia
Course - Copilot for Finance and Accounting Professionals
The background / theory of LLMs, the exercise
Joanne Wong - IPG HK Limited
Course - Applied AI for Financial Statement Analysis & Reporting
Interaction with the audience, not too technical
