Rising Operational Cost
Uncontrolled token usage, redundant model calls, and no caching strategy can turn a working prototype into an unsustainable AI bill. Learn to cut inference cost without cutting quality.
Global Certification
LLMOps Course & Certification | AI Production Deployment Training
This LLMOps course is built for engineers who already have a working LLM prototype and need to take it into production. Across 12 hands-on modules, you'll learn to deploy, monitor, secure, and scale large language model systems, from GPU infrastructure and high-performance model serving to RAG pipelines, AI agents, LLM evaluation, guardrails and CI/CD. Built for anyone targeting an LLMOps Engineer role or upgrading their team's AI infrastructure, with real production tooling (vLLM, LangGraph, Ragas, LangSmith, NeMo Guardrails) rather than theory alone.
Structured learningHands-on practiceProfessional outcomes
Accredited By
Explore Technologies and Practices Used Across Modern AI Organizations
Why This Skill Matters Now
LLMOps matters now because most AI projects don't fail at the model; they fail after it. A working prototype means little if it can't survive real traffic, control its own cost, or resist a bad actor. This LLMOps training is designed to close that exact gap: turning working demos into production systems that are reliable, affordable, and safe to run.
Unpredictable Production Risk
Hallucinations, prompt injection, and silent RAG failures don't show up in a demo; they show up in production. Build the evaluation and guardrail systems that catch them first.
Slow Delivery
Manual prompt tuning and ad-hoc deployment turn every model update into a fire drill. Use repeatable LLMOps pipelines to ship changes safely and fast.
Is This LLMOps Course Right For You?
The LLMOps course is designed for professionals who want to move beyond building AI prototypes and learn how to deploy, monitor, secure, and optimize LLM applications in production. The path also helps professionals understand the skills and practices relevant to pursuing LLMOps certification.
✓ Perfect For You If...
- ✓You've built an LLM prototype (RAG app, chatbot, agent) and now need to make it production-safe
- ✓You're comfortable learning through real deployment labs, not just lecture videos
- ✓You want to control AI infrastructure costs, not just get a model working
- ✓You're targeting an LLMOps, MLOps, or AI Engineer role and need demonstrable, project-based skills
✕ Not For You If...
- ✕You're looking for a theoretical intro to what LLMs are (start with our "What is LLMOps" guide instead)
- ✕You want passive video watching with no hands-on labs or assessments
- ✕You're not ready to work with real tools (RAG pipelines, guardrails, observability dashboards)
- ✕You have no prior exposure to APIs, prompting, or basic ML/AI concepts
Complete Course Syllabus PDF
Includes the detailed learning path, module structure and technical prerequisites.
What You Will Build
You'll build what a production LLMOps course should actually teach: a cost-optimized deployment pipeline, a guardrail layer that blocks misuse, and an observability dashboard that catches failures before your users do.
Cost & Latency Optimization Pipeline
Build a routing system that sends simple queries to cheaper, faster models and caches repeated answers, cutting inference cost without sacrificing response quality.
AI Guardrails & Security Layer
Implement a defense layer using tools like NeMo Guardrails or LlamaGuard to block prompt injection attacks and prevent off-brand or hallucinated responses before they reach users.
Observability Dashboard
Set up tracing and debugging for RAG pipeline failures using tools like LangSmith or Phoenix, so when something breaks in production, you can find out why in minutes, not hours.
Student Showcase
This is what a completed LLMOps course looks like in practice, not toy examples, but production systems learners actually shipped.
LLM Cost & Latency Optimization Pipeline
An existing AI customer support tool was taking too long to respond and burning through API credits by sending every simple query to an expensive, heavy-weight model. The student implemented a semantic caching layer to instantly answer repeated questions, and built a model-router that automatically directed simple queries to a cheaper, faster model (like Llama 3 8B) and only routed complex queries to GPT-4 Reduced average response latency by 60% and cut daily token API costs in half, without degrading the quality of the AI's answers.
Enterprise AI Guardrails & Security Shield
A company’s internal AI assistant was vulnerable to prompt injection attacks and would occasionally hallucinate confidential data or answer off-topic questions. Instead of trying to rewrite the base application, the student deployed an independent security layer (using tools like NeMo Guardrails or LlamaGuard). They established strict input/output filters to block malicious "jailbreaks" and automatically intercept toxic or off-brand responses before they reached the user. Secured a vulnerable AI endpoint against 99% of common prompt injections and ensured 100% compliance with company brand guidelines.
"Black Box" Observability Dashboard
Engineering teams were receiving user complaints about a Retrieval-Augmented Generation (RAG) bot giving wrong answers, but had no way to track where the failure was happening (was it a bad prompt, or bad document retrieval?). The student integrated a full tracing and observability suite (such as LangSmith or Phoenix) into the existing, unmonitored architecture. They created a live dashboard that logged every step of the AI's thought process, flagged errors automatically, and monitored retrieval accuracy. Eliminated 'black box' AI failures by giving engineering teams a dashboard to pinpoint and debug hallucination errors in minutes instead of days.
⭐ Curriculum Overview
Your LLMOps Learning Path
Progress through foundational concepts, production workflows, and hands-on labs designed to prepare you for real-world LLMOps challenges.
Module 01Free access
Foundations: From ML Ops to LLM Ops
Master the LLMOps lifecycle, from development and evaluation to deployment, monitoring, and continuous optimization of AI applications. Build a strong foundation in essential LLM terminology and industry concepts to confidently design, deploy, and manage production-ready LLM solutions.
▾
Module 02Free access
Model Selection & Serving Architecture
Compare proprietary APIs against open-weight models, and learn to stand up local inference servers while navigating GPU memory bottlenecks. Build the judgment to choose the right model and serving strategy for latency, cost, and scale.
▾
Module 03Free access
Prompt & Context Engineering at Scale
Move beyond basic prompting to build dynamic prompt templating systems, enforce structured JSON outputs, and orchestrate automated regression tests so prompts stay reliable as your application evolves.
▾
Module 04Free access
Retrieval-Augmented Generation (RAG) Pipelines
Build end-to-end retrieval-augmented generation pipelines, master chunking strategies, hybrid re-ranking, and vector database integration (pgvector, Pinecone) to connect LLMs reliably to external and enterprise data.
▾
Module 05Free access
Fine-Tuning & Customization
Learn when to fine-tune versus when to prompt. Apply parameter-efficient fine-tuning (LoRA) and curate high-quality datasets to customize model behavior for specific use cases.
▾
Module 06Free access
Evaluation & Quality Assurance
Replace guesswork with data, construct golden datasets, use LLM-as-a-judge evaluation patterns, and build CI gating that catches quality regressions before they reach production.
▾
Module 07Free access
Production Infrastructure & MLOps Integration
Containerize and orchestrate LLM deployments, integrate caching strategies and model registries, and connect your systems into existing Kubernetes/Docker and CI/CD workflows.
▾
Module 08Free access
Observability, Monitoring & Cost Management
Instrument applications with tracing and observability tooling (LangSmith, Phoenix), track model drift and error rates, and monitor cost-per-query so inference spend stays under control at scale.
▾
Module 09Free access
Security, Safety & Governance
Red-team your applications to find vulnerabilities, implement guardrails against prompt injection using tools like NeMo Guardrails or LlamaGuard, and apply PII redaction to protect user privacy and brand reputation.
▾
Module 10Free access
Scaling, Multi-Model Systems & Capstone
Architect multi-model routing and disaster recovery for production-scale systems, then bring everything together in a capstone project, a deployment-ready AI application demonstrating the full LLMOps lifecycle.
▾
Certification Exam
Exam Details
Review the key certification exam information before you begin your preparation.
Exam Questions42
Exam FormatMultiple Choice
LanguageEnglish
Passing Score70%
Duration90 min
ProctoredYes
Certification Validity5 Years
Complimentary RetakeYes
Learn From Practitioners
Ayush Kulshreshtha
AI Coach & Consultant
Ayush Kulshreshtha brings a practical, industry-focused approach to LLMOps Training. He has designed the curriculum around real-world AI production patterns, helping learners understand how organizations move from LLM prototypes and pilots to secure, scalable, production-ready AI systems. His training approach combines technical expertise, hands-on learning, strategic thinking, and real-world use cases, enabling professionals to design AI solutions that align with business goals and enterprise requirements.
✓ Practitioner-led✓ Hands-on guidance✓ Real-world implementation
👥 Elite Network & Support
Sharpen Your LLMOps Skills Through Hands-On Practice
Move through the LLMOps certification with guided expert sessions, real deployment case studies, practical tooling, and assessments built to test whether you can actually ship production-ready LLM systems.
Real Deployment BreakdownsHow cost-efficient, secure LLM systems go from prototype to production.
Working With LLMOps ToolsHands-on practice with LangSmith, Phoenix, and NeMo Guardrails.
Expert-Led SessionsRecorded walkthroughs from LLMOps practitioners on deployment and monitoring.
📈 Alumni Spotlight
From LLM Prototype to Production Engineer
“The cost-optimization module wasn't theoretical; I built the same routing system for my team's support bot and cut our API bill in half within a week of finishing the course.”
Completed the LLMOps Certification, now leading AI infrastructure at a SaaS company
Learner Success StoryJessica Devis
Trusted by AI Professionals
See how learners apply LLMOps skills to real production environments and career growth.
Professional Bonuses
Access exclusive resources designed to strengthen your practical skills and accelerate your career with our LLMOps course. Get valuable learning materials, practical resources, and career-focused guidance to help you confidently apply LLMOps concepts in real-world projects.
LLMOps Best Practices Checklist
A comprehensive checklist for deploying, monitoring, and maintaining LLMs in production environments. ($79 Value)
Production Deployment Templates
Ready-to-use configuration files and scripts for common LLMOps infrastructure patterns. ($129 Value)
Private Alumni Network
Lifetime access to peer learning, job opportunities, and industry connections with other LLMOps professionals. (Priceless Value)
Invest in Your AI Career
Choose the plan that fits your learning goals.
Enrollment Capacity: Limited support capacity is available for personalized practical guidance.
Free Access
Get started with foundational content and explore the learning path.
Free
Start Free- ✓Study material for all 10 modules
- ✓Slide decks and video lessons
- ✓Real-world use cases
- ✓Basic learning support
Most Popular
Professional Plan
Complete LLMOps mastery with all modules, labs, assessments, and lifetime access.
$199
Enroll Now- ✓Hands-on production labs
- ✓Certification-ready assessments and practice exams
- ✓3 production projects + capstone
- ✓AI tutor for every module
- ✓GSDC certification exam and certificate
- ✓Premium support and lifetime access
🏢
Train Your AI Team Together
Take your engineering team from LLM prototypes to production-ready systems, with group pricing, progress tracking and one point of contact for enrollment.
Compare Access
Free Access vs Professional Plan
Every module is free to study. The Professional Plan adds the practice, proof and certification that employers look for.
CompareFeatures
Explore firstFree Access
Unlock everythingProfessional PlanBest Value
Complete study material
Slide decks, video lessons and use cases for all 10 modules. Learn every LLMOps concept at your own pace.
Slide decks, video lessons and use cases for all 10 modules. Learn every LLMOps concept at your own pace.
✓
✓
Hands-on production labs
Work with real production tooling: serve models, build RAG pipelines, add guardrails and trace failures. These are skills you can use at work the next day.
Work with real production tooling: serve models, build RAG pipelines, add guardrails and trace failures. These are skills you can use at work the next day.
✕
✓
Certification-ready assessments
Quizzes, themed challenges and full practice exams that show you exactly where you stand before the real exam.
Quizzes, themed challenges and full practice exams that show you exactly where you stand before the real exam.
✕
✓
Production projects
Three production projects (a cost and latency optimization pipeline, an AI guardrails layer and an observability dashboard) plus a capstone you can show employers.
Three production projects (a cost and latency optimization pipeline, an AI guardrails layer and an observability dashboard) plus a capstone you can show employers.
✕
✓
AI tutor
Ask questions on any module and get instant, focused answers while you learn.
Ask questions on any module and get instant, focused answers while you learn.
✕
✓
GSDC certification
A 42-question proctored exam with a complimentary retake. The credential stays valid for 5 years.
A 42-question proctored exam with a complimentary retake. The credential stays valid for 5 years.
✕
✓
Learning support and community
Get unstuck quickly on practical work and connect with other AI and LLMOps engineers.
Get unstuck quickly on practical work and connect with other AI and LLMOps engineers.
Basic
Premium
Lifetime access
Keep your labs, projects and materials, and come back whenever you need a refresher.
Keep your labs, projects and materials, and come back whenever you need a refresher.
✕
✓
Ready for the complete learning journey?Get every module, lab, assessment, project and certification benefit.
View Professional Plan
Risk-Free Enrollment
30-Day Money-Back Guarantee
If the professional learning experience doesn't meet your expectations, request a full refund within 30 days of enrollment.
Frequently Asked Questions
Everything you need to know before starting your LLMOps course.
Wondering how this hub fits into the full certification?
The main course page explains the 12-module curriculum, eligibility, the proctored exam and the 5-year certification.