LLMOps-Large Language Model Operations Mastery
Enroll in LLMOps-Large Language Model Operations Mastery. Get expert training, hands-on projects, certification & career support. Learn job-ready skills with Eklabya.
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This Course Includes:
- On-demand Sessions
- Downloadable Resources
- Portfolio Website
- Live Industry Project
- Freelance Projects
- Lifetime eKlabya Membership
Certificate of Completion
Validate your skills and enhance your resume upon completing all modules.
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“Excellent training center for SAP Material Management certification courses. The sessions were interactive, and the placement support helped me gain confidence for interviews. The practical assignments made learning easy and effective.”
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“Myself Ritika I have learned Data Science and Power BI form Eklabya, As students I have experienced well structured training and practical from here. The trainer explained every concept step-by-step clear my all doubts with practical examples and real-time scenario, thats helped me build my knowledge strong and improve my skills in data science”
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Sheeba Jaidiya
Eklabya Verified Learner
“Excellent training center for SAP Material Management certification courses. The sessions were interactive, and the placement support helped me gain confidence for interviews. The practical assignments made learning easy and effective.”
Vaibhav Thakur
Eklabya Verified Learner
“Excellent curriculum and amazing support from the team. I landed my first MNC job within two months of completing the program. Thank you Eklabya!”
Ritika Bhadani
Eklabya Verified Learner
“Myself Ritika I have learned Data Science and Power BI form Eklabya, As students I have experienced well structured training and practical from here. The trainer explained every concept step-by-step clear my all doubts with practical examples and real-time scenario, thats helped me build my knowledge strong and improve my skills in data science”
Amit Verma
Eklabya Verified Learner
“I had a great learning experience with Eklabya while pursuing Data Science. The course was well-structured, practical, and helped me understand important concepts with real-world applications. The guidance and support from the trainers were really helpful throughout the learning journey. Highly recommended for anyone looking to build a career in Data Science!”
Sheeba Jaidiya
Eklabya Verified Learner
“Excellent training center for SAP Material Management certification courses. The sessions were interactive, and the placement support helped me gain confidence for interviews. The practical assignments made learning easy and effective.”
Vaibhav Thakur
Eklabya Verified Learner
“Excellent curriculum and amazing support from the team. I landed my first MNC job within two months of completing the program. Thank you Eklabya!”
Ritika Bhadani
Eklabya Verified Learner
“Myself Ritika I have learned Data Science and Power BI form Eklabya, As students I have experienced well structured training and practical from here. The trainer explained every concept step-by-step clear my all doubts with practical examples and real-time scenario, thats helped me build my knowledge strong and improve my skills in data science”
Amit Verma
Eklabya Verified Learner
“I had a great learning experience with Eklabya while pursuing Data Science. The course was well-structured, practical, and helped me understand important concepts with real-world applications. The guidance and support from the trainers were really helpful throughout the learning journey. Highly recommended for anyone looking to build a career in Data Science!”
Sheeba Jaidiya
Eklabya Verified Learner
“Excellent training center for SAP Material Management certification courses. The sessions were interactive, and the placement support helped me gain confidence for interviews. The practical assignments made learning easy and effective.”
Vaibhav Thakur
Eklabya Verified Learner
“Excellent curriculum and amazing support from the team. I landed my first MNC job within two months of completing the program. Thank you Eklabya!”
Ritika Bhadani
Eklabya Verified Learner
“Myself Ritika I have learned Data Science and Power BI form Eklabya, As students I have experienced well structured training and practical from here. The trainer explained every concept step-by-step clear my all doubts with practical examples and real-time scenario, thats helped me build my knowledge strong and improve my skills in data science”
Amit Verma
Eklabya Verified Learner
“I had a great learning experience with Eklabya while pursuing Data Science. The course was well-structured, practical, and helped me understand important concepts with real-world applications. The guidance and support from the trainers were really helpful throughout the learning journey. Highly recommended for anyone looking to build a career in Data Science!”
Sheeba Jaidiya
Eklabya Verified Learner
About This Course
Unlock the secrets of bringing Generative AI into production. While many can build a ChatGPT prototype, very few can manage, scale, and monitor Large Language Models in a real-world environment. Our LLMOps Mastery course is a high-level engineering program designed to teach you the industrial-grade lifecycle of LLM applications. You will master Retrieval Augmented Generation (RAG) at scale, learn the intricacies of Fine-Tuning (PEFT/LoRA), and build robust automated pipelines using tools like LangChain, LangSmith, and Weights & Biases. We focus heavily on 'AI Trust'—teaching you how to handle hallucinations, implement safety guardrails, and optimize token costs. Whether you are a DevOps engineer moving into AI or a Data Scientist aiming for production roles, this course provides the technical blueprint for the future of AI operations.
Who is this course for?
Full Curriculum
Data Engineering for LLMs: RAG at Scale
Orchestration & AI Agent Design
Observability, Monitoring & Tracing
Deployment & Infrastructure at Scale
Skills Student Will Learn
- LLM Lifecycle Management
- RAG Architecture
- Fine-Tuning (LoRA/QLoRA)
- Vector Databases
- AI Observability & Tracing
- Prompt Engineering for Scale
- LangChain / LangGraph
- Model Evaluation (RAGAS)
- Safety Guardrails
- Python for AI
Topics Student Will Learn
- Implement automated evaluation frameworks to measure AI accuracy and drift.
- Set up full observability to trace and debug complex multi-step AI chains.
- Deploy LLMs using modern inference engines for high throughput and low latency.
- Manage the operational costs and security risks associated with production AI.
Requirements
No prerequisites available for this course.
Frequently Asked Questions
MLOps focuses on training models from scratch. LLMOps focuses on managing pre-trained 'Foundation Models,' prompt versioning, and complex RAG retrieval pipelines.
This course equips you with practical LLMOps skills, including deploying LLMs, implementing Retrieval-Augmented Generation (RAG), fine-tuning models using PEFT and LoRA, building automated evaluation pipelines, monitoring model performance, optimizing token usage, and implementing AI safety guardrails for production-ready applications.
The course introduces industry-relevant LLMOps tools and frameworks such as LangChain, LangSmith, Weights & Biases, Retrieval-Augmented Generation (RAG) workflows, modern inference engines, and automated evaluation frameworks used to build, deploy, and monitor production AI applications.
Yes. The course covers Retrieval-Augmented Generation (RAG) for building knowledge-aware AI applications and teaches parameter-efficient fine-tuning techniques such as PEFT and LoRA to customize Large Language Models efficiently while reducing computational costs.
You will learn how to implement automated evaluation frameworks, monitor model accuracy and drift, trace complex AI workflows, debug multi-step AI chains, and improve the overall reliability and performance of production LLM applications.
No specific prerequisites are required. The course is suitable for anyone interested in learning LLMOps. However, a basic understanding of programming, AI concepts, or DevOps can help learners grasp advanced production workflows more effectively.
Yes. The course focuses on production-ready LLM deployment using modern inference engines, covering scalability, low-latency serving, observability, security, and operational best practices for real-world AI applications.
The curriculum emphasizes AI Trust by teaching strategies to reduce hallucinations, implement safety guardrails, monitor model behavior, and optimize token consumption, helping learners build secure, cost-effective, and reliable AI systems.
Yes. This course is designed for DevOps engineers transitioning into AI, Data Scientists looking to deploy models in production, AI engineers, and professionals who want to build expertise in Large Language Model Operations.
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