Build AI Agents with Microservices and RAG

Are you looking to automate complex financial reconciliation processes? This course will guide you through building a sophisticated AI agent using a microservices architecture. You will gain hands-on experience with Retrieval-Augmented Generation (RAG) systems, large language models, and essential tools for distributed applications. Understand the core principles of creating intelligent agents that can process and reconcile financial data efficiently. You will learn to design and implement a robust system capable of handling real-world automation challenges. What you'll learn: * Understand the fundamentals of AI agents and microservice architecture. * Implement Retrieval-Augmented Generation (RAG) for enhanced AI reasoning. * Develop intelligent financial reconciliation logic using Python and ML models. * Integrate message queuing systems like Kafka for asynchronous communication. * Containerize your applications using Docker for consistent deployment. * Orchestrate microservices with Kubernetes for scalability and resilience. * Deploy your AI agent to a cloud environment. This course covers the essential concepts from foundational definitions to practical implementation, preparing you to build and deploy your own AI-powered automation solutions. This course is designed for beginners with no prior experience in AI agent development or microservices. Start building your intelligent automation system today.