Integration and Deployment of GenAI Models

About this course

The gap between creating GenAI models and deploying them into production is where most AI initiatives fail. While countless courses teach you how to build models, few prepare you for the critical engineering challenges that determine whether your AI will reach users or remain trapped in development. This comprehensive course bridges that gap, transforming you from an AI enthusiast into a complete GenAI engineer.

Designed for developers and engineers ready to move beyond theory, this hands-on course guides you through the entire deployment lifecycle of generative AI systems. You'll build real-world applications using today's most powerful AI platforms while mastering the infrastructure that makes them reliable, scalable, and production-ready.

Through practical, project-based learning, you'll:

Master API Integration - Build seamless connections between GenAI models and applications using FastAPI, enabling powerful AI features with clean, efficient interfaces

Containerize AI Systems - Package complete GenAI applications with Docker to ensure consistent performance across any environment

Orchestrate with Kubernetes - Scale your GenAI deployments effectively, managing resources and ensuring reliability even under demanding workloads

Deploy Production Applications - Create and deploy four complete GenAI applications including a text summarizer, AI chatbot, audio transcription service, and an intelligent PDF chat system

Work with Leading AI Platforms - Gain hands-on experience with Cohere, Amazon Bedrock, AssemblyAI, and Google Gemini, building valuable skills with industry-standard tools

Each section builds toward complete, working applications that demonstrate real-world deployment patterns. You'll create deployable solutions for t

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