Building Conversational AI Agents with Cloud Services

Do you want to leverage powerful large language models (LLMs) to create automated, intelligent assistants? Combining cloud infrastructure with AI services allows developers to deploy scalable, functional conversational agents quickly. This course teaches you the foundational architecture for building and deploying a simple AI bot, focusing on the connection points between external messaging platforms, cloud serverless functions, and AI APIs. You will understand the workflow necessary to turn a raw LLM into a useful, context-aware assistant. What you'll learn: * Understand the core components of a serverless AI bot architecture, including functions and API gateways. * Configure API Gateways to securely handle incoming requests from external messaging platforms. * Practice writing serverless function code to orchestrate bot logic and manage conversation state. * Integrate third-party LLM services using API calls to generate contextually relevant responses. * Apply the Retrieval-Augmented Generation (RAG) pattern to ground AI responses in specific knowledge data. * Deploy and manage configuration for your serverless bot application using standard cloud practices. The curriculum begins by defining serverless architecture and API integration essentials. We then move into practical implementation, showing how to connect an external messenger to a serverless function, integrate the AI service, and establish a reliable conversational workflow. This course is designed for beginners interested in cloud development, serverless computing, and artificial intelligence applications. No prior experience with serverless platforms or AI APIs is required, just basic programming knowledge. Start building your first intelligent cloud-based agent today.