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Unlock the world of MLOps for Large Language Models (LLMs) in this student-exclusive deep-dive session! From model training to deployment, monitoring, and scaling — learn how AI projects are managed end-to-end in real industry environments. This session breaks down the tools, workflows, and best practices needed to build and maintain LLM systems that are reliable, efficient, and production-ready. 🔥 What You’ll Learn What is MLOps and why it matters for LLMs Pipeline architecture for LLM development Data preparation, versioning & model tracking Fine-tuning workflows for LLMs Deploying Large Language Models in production Monitoring model drift, performance & reliability Tools used in industry (MLflow, Kubeflow, HuggingFace, Docker, CI/CD, etc.) 🎓 Who Is This Session For? Students, beginners, and aspiring AI/ML engineers looking to understand how real-world LLM systems are built, deployed, and maintained. 🚀 Don’t forget to Like, Share & Subscribe for more AI, ML, and MLOps content! For more details: Facebook : https://www.facebook.com/Datavalleyai/ Instagram : https://www.instagram.com/datavalley.ai/ Twitter : https://twitter.com/Datavalley_ai LinkedIn : https://www.linkedin.com/company/datavalley-ai/ Website : https://datavalley.ai/ WhatsApp : https://api.whatsapp.com/send/?phone=919256899199 Also, do not forget to join us on our website's : 1. Community Site: https://community.datavalley.ai/ 2. News Site: https://news.datavalley.ai/ and be the first to hear about the latest news and updates. 📧 For any inquiries or collaboration opportunities, please contact us at : info@datavalley.ai 🔥 Interested in Attending Live Classes? Call Us: IN - +91 9256899199 /9138 981 888 / US - +1 3027226197