Get in Touch
 Duration 14 hours

Course Outline

Introduction to Edge AI in the Financial Sector

  • Overview of Edge AI concepts and their specific applications in finance
  • Analyzing the benefits and challenges of adopting Edge AI in banking operations
  • Examining case studies of successful Edge AI integrations in the financial industry

Establishing the Edge AI Environment

  • Installation and configuration of essential Edge AI tools
  • Integration of financial data sources and collection infrastructure
  • Introduction to key Edge AI frameworks and libraries
  • Practical exercises focused on setting up the development environment

Fraud Detection Utilizing Edge AI

  • Fundamental concepts of fraud detection in financial contexts
  • Development of AI models capable of real-time fraud identification
  • Implementation of advanced anomaly detection systems
  • Hands-on exercises dedicated to fraud detection mechanisms

Improving Customer Service Through Edge AI

  • Overview of customer service dynamics within financial services
  • Application of AI techniques for personalized customer engagement
  • Deployment of AI-driven chatbots and virtual assistants
  • Practical exercises for building customer service applications

Risk Management with Edge AI

  • Introduction to modern risk management strategies
  • Leveraging AI for real-time risk assessment and mitigation efforts
  • Implementation of AI-powered decision support systems
  • Hands-on exercises to practice risk management applications

Deployment and Management of Edge AI Solutions

  • Deploying AI models onto financial edge devices
  • Ongoing monitoring and maintenance of Edge AI systems
  • Troubleshooting and performance optimization of deployed models
  • Practical exercises covering deployment and system management

Tools and Frameworks for Financial Edge AI

  • Survey of available tools and frameworks (including TensorFlow Lite, OpenVINO)
  • Application of TensorFlow Lite for financial AI use cases
  • Practical exercises involving optimization tools

Real-World Applications and Case Studies

  • Review of successful financial Edge AI projects
  • Discussion of industry-specific use cases and scenarios
  • Hands-on project to build and optimize a real-world financial AI application

Summary and Recommended Next Steps

Requirements

  • A solid grasp of fundamental AI and machine learning principles
  • Familiarity with financial services landscapes and fintech application development
  • Foundational programming proficiency, with Python being the recommended language

Target Audience

  • Finance professionals
  • Fintech developers
  • AI specialists

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories