Course Outline

Introduction to Domain-Specific Fine-Tuning

  • Overview of fine-tuning techniques for government and private sector applications
  • Challenges specific to the financial domain for government operations
  • Case studies of AI implementation in finance for government oversight and efficiency

Pre-trained Models for Financial Applications

  • Introduction to popular pre-trained models, such as GPT and BERT, for use in financial analysis for government agencies
  • Selecting the most appropriate models for specific financial tasks for government
  • Data preparation methods tailored for fine-tuning in financial contexts for government applications

Fine-Tuning for Key Financial Tasks

  • Enhancing fraud detection using machine learning models for government oversight and security
  • Conducting risk assessment with predictive modeling for government financial management
  • Developing automated financial advisory systems to support government decision-making

Addressing Financial Data Challenges

  • Strategies for handling sensitive and imbalanced data in government financial datasets
  • Ensuring robust data privacy and security measures for government applications
  • Integrating financial regulations into AI workflows for government compliance

Ethical and Regulatory Considerations

  • Promoting ethical AI practices within the financial industry for government agencies
  • Compliance with regulatory standards such as GDPR and SOX in government operations
  • Maintaining transparency and accountability in AI models for government use

Scaling and Deploying Models

  • Optimizing models for efficient deployment in production environments for government systems
  • Monitoring and maintaining model performance to ensure reliability for government operations
  • Best practices for scaling financial applications to meet the needs of government agencies

Real-World Applications and Case Studies

  • Implementing fraud detection systems in government financial oversight
  • Developing risk modeling for investment portfolios managed by government entities
  • Leveraging AI-powered customer service solutions in government financial services

Summary and Next Steps

Requirements

  • Basic understanding of machine learning for government applications
  • Familiarity with Python programming
  • Knowledge of financial concepts and terminology

Audience

  • Financial analysts for government agencies
  • AI professionals in the public sector finance domain
 21 Hours

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Upcoming Courses

Domain-Specific Fine-Tuning for Finance

2026-01-20 09:30
21 hours
Louis, MO - Regus – Central West End
$ 4054 (Online)
$ 5854 (Classroom)

Domain-Specific Fine-Tuning for Finance

2026-02-03 09:30
21 hours
Chattanooga, TN – Regus Tallan Financial Center
$ 4054 (Online)
$ 5854 (Classroom)

Domain-Specific Fine-Tuning for Finance

2026-02-17 09:30
21 hours
Topeka, KS - Omni Circle
$ 4054 (Online)
$ 5854 (Classroom)

Domain-Specific Fine-Tuning for Finance

2026-03-03 09:30
21 hours
Trenton, NJ – Base Camp Trenton
$ 4054 (Online)
$ 5854 (Classroom)

Domain-Specific Fine-Tuning for Finance

2026-03-17 09:30
21 hours
Tucson, AZ - Regus – One South Church Downtown
$ 4054 (Online)
$ 5854 (Classroom)

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