LLMOps And AIOps Bootcamp With 9+ End To End Projects

Are you ready to take your **Generative AI and LLM (Large Language Model)** skills to a production-ready level? This comprehensive hands-on course on LLMOps is designed for developers, data scientists, MLOps engineers, and AI enthusiasts who want to build, manage, and deploy scalable LLM applications using cutting-edge tools and modern cloud-native technologies. In this **LLMOps And AIOps Bootcamp With 9+ End To End Projects course**, you will learn how to bridge the gap between building powerful LLM applications and deploying them in real-world production environments using GitHub, Jenkins, Docker, Kubernetes, FastAPI, Cloud Services (AWS & GCP), and CI/CD pipelines. We will walk through multiple end-to-end projects that demonstrate how to operationalize HuggingFace Transformers, fine-tuned models, and Groq API deployments with performance monitoring using Prometheus, Grafana, and SonarQube. You'll also learn how to manage infrastructure and orchestration using Kubernetes (Minikube, GKE), AWS Fargate, and Google Artifact Registry (GAR).

What you'll learn:

• Build and deploy real-world AI apps using Langchain, FAISS, ChromaDB, and other cutting-edge tools.
• Set up CI/CD pipelines using Jenkins, GitHub Actions, CircleCI, GitLab, and ArgoCD.
• Use Docker, Kubernetes, AWS, and GCP to deploy and scale AI applications.
• Monitor and secure AI systems using Trivy, Prometheus, Grafana, and the ELK Stack