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Course Outline
Introduction to Edge AI in Financial Services
- Overview of Edge AI and its applications in finance.
- Benefits and challenges of using Edge AI in banking.
- Case studies of successful Edge AI applications in finance.
Setting Up the Edge AI Environment
- Installing and configuring Edge AI tools.
- Integrating financial data sources and collection systems.
- Introduction to relevant Edge AI frameworks and libraries.
- Hands-on exercises for environment setup.
Fraud Detection with Edge AI
- Introduction to fraud detection.
- Developing AI models for real-time fraud detection.
- Implementing anomaly detection systems.
- Hands-on exercises for fraud detection.
Enhancing Customer Service Using Edge AI
- Overview of customer service in financial services.
- AI techniques for personalized customer interactions.
- Implementing AI-driven chatbots and virtual assistants.
- Hands-on exercises for customer service applications.
Risk Management with Edge AI
- Introduction to risk management.
- Using AI for real-time risk assessment and mitigation.
- Implementing AI-driven decision support systems.
- Hands-on exercises for risk management.
Deploying and Managing Edge AI Solutions
- Deploying AI models on financial edge devices.
- Monitoring and maintaining Edge AI systems.
- Troubleshooting and optimizing deployed models.
- Hands-on exercises for deployment and management.
Tools and Frameworks for Financial Edge AI
- Overview of tools and frameworks (e.g., TensorFlow Lite, OpenVINO).
- Using TensorFlow Lite for financial AI applications.
- Hands-on exercises with optimization tools.
Real-World Applications and Case Studies
- Review of successful financial Edge AI projects.
- Discussion of industry-specific use cases.
- Hands-on project for building and optimizing a real-world financial AI application.
Summary and Next Steps
Requirements
- A foundational understanding of AI and machine learning concepts.
- Experience working with financial services and fintech applications.
- Basic programming skills (Python is recommended).
Audience
- Finance professionals.
- Fintech developers.
- AI specialists.
14 Hours
Testimonials (1)
That we can cover advance topic and work with real-life example
