LLMOps Masterclass 2026 – Generative AI, MLOps & AIOps

About This Course

This course focuses on building, deploying, and managing large language model (LLM) applications using modern AI and MLOps practices. It covers generative AI concepts, prompt engineering, and production deployment using industry tools.

Quick Details

• Rating: 4.6 / 5
• Students: 7,059
• Duration: 16.5 Hours
• Articles: 4
• Language: English
• Certificate: Yes
• Access: Lifetime

What You’ll Learn

• Understand generative AI concepts and real-world applications
• Learn differences between generative and traditional AI models
• Master prompt engineering techniques and architecture
• Build LLM applications using ChatGPT and Hugging Face
• Deploy AI applications using FastAPI, Docker, and Kubernetes
• Implement CI/CD pipelines using GitHub Actions
• Monitor LLM models in production environments
• Learn LLMOps concepts including version control and deployment workflows
• Apply industry best practices for AI development and operations

AI System Design & MLOps: From Raw Data to AWS Kubernetes

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Key Topics Covered

• Generative AI
• LLMOps
• Prompt Engineering
• MLOps & AIOps
• Deployment & CI/CD
• Model Monitoring

Why This Course

This course provides a complete understanding of how LLM-based applications are built and deployed in real environments. It combines theory with hands-on implementation using modern tools.

Who Should Take This

• AI and machine learning engineers
• Data scientists working with LLMs
• Developers building AI applications
• Anyone interested in generative AI and deployment

Final Thoughts

A well-rounded course for learning LLMOps and generative AI deployment. It is suitable for learners who want to build and manage production-ready AI systems using modern tools and workflows.