AI-powered Python Applications: Building APIs for Generative AI Models

Let's build secure, high-performance APIs for AI applications using Python! This course covers REST API basics, integrating generative AI models, optimizing model inference, implementing security measures, and monitoring API performance for real-time AI capabilities. You'll explore how to integrate Python-based models with API backends and enhance performance through model inference techniques, batching, and optimization. In this course, AI-powered Python Applications: Building APIs for Generative AI Models, you'll harness the power of AI in production environments. First, you'll dive into creating REST APIs that effectively serve generative AI models, such as text generation, summarization, and data enrichment. Next, you'll discover how to optimize model inference through techniques like batching and caching to achieve high performance. Finally, you'll implement critical security measures, including user authentication, authorization, and rate-limiting, to ensure API reliability in real-time applications. By the end of this course, you’ll gain insights into creating scalable, secure APIs that bring generative AI functionalities into real-world application, providing seamless, AI-driven experiences in applications that require real-time responses.