BestsellerAI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents
Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI, RAG, LoRA and AI Agents.
Deploy AI to AWS, GCP, Azure, Vercel with MLOps, Bedrock, SageMaker, RAG, Agents, MCP: scalable, secure and observable.
This is the course that more of my students have asked for than any other course — put together.One student called it:“The missing course in AI.”This course is for:EntrepreneursEnterprise engineers…and everyone in between.It’s not just about RAG — although we’ll work with RAG.It’s not just about Agents — but there will be many Agents.It’s not just about MCP — but yes, there will be plenty of MCP too.This course is about:RAG, Agents, MCP, and so much more… deployed to production.Live.Enterprise-grade.Scalable, resilient, secure, monitored — and explained.You’ll ship real-world, production-grade AI with LLMs and agents across Vercel, AWS, GCP, and Azure, going deepest on AWS.Across four weeks you’ll take four products to production:Week 1You’ll launch a Next.js SaaS product on Vercel and AWS,with AWS App Runner and Clerk for user management and subscriptions. Week 2You’ll become an AI platform engineer on AWS,deploying serverless infrastructure using:Lambda, Bedrock, API Gateway, S3, CloudFront, Route 53Write Infrastructure as Code with TerraformSet up CI/CD pipelines with GitHub Actions— for hands-free deployments and one-click promotions.Week 3You’ll gain broad industry skills for GenAI in production:Deploy a Cyber Security Analyst agent with MCP to Azure & GCPStand up SageMaker inferenceBuild data ingest to S3 vectorsDeploy a Researcher Agent using OpenAI OSS models on Bedrock + MCPWeek 4You’ll go
Best for: all level learners who want one guided path through Data Science. Skip it if: You already work professionally in Data Science and need advanced architecture patterns.
4 sections · 124 lectures · 18.5 hours of video · updated 11/2026
Suits: Complete beginners, career switchers, and self-taught devs who want structure.
Needs: While it’s ideal if you can code in Python and have some experience working with LLMs, this course is designed for a very wide audience, regardless of background. I’ve included a whole folder of self-study labs that cover foundational technical and programming skills. If you’re new to coding, there’s only one requirement: plenty of patience! The course runs best if you have a small budget for APIs and Cloud Providers of a few dollars. But we monitor expenses at every point, and it's always a personal choice.
Ligency — Join 4M+ learners who study with Ligency. With a 4.6 instructor rating, >1M reviews, and 127 courses in 12 languages, we help engineers, leaders, and teams master the skills that power today’s AI revolution - then ship real results. We start where the real world starts: with large language models and the products they power. You’ll learn the foundations of AI and Generative AI (gen AI), then ship production-grade systems - chatbots, copilots, automations, and AI agents. We go deep on LLM engineering: retrieval (RAG), evaluation, observability, safety, and the patterns teams use to run agentic systems at scale. Our stack is practical and current. You’ll prototype fast with Python, LangChain, and LangGraph; explore models from OpenAI, Gemini, and Claude (including Claude Code); fine-tune and serve with Hugging Face and Ollama; and take it to production on AWS - from Bedrock to event-driven services. Need automation? We wire it together with n8n, clean interfaces, and CI/CD. Along the way you’ll master prompt engineering that holds up under load. Where this leads: roles that ship. AI Engineer and LLM Engineer for those who love building; platform and MLOps paths for those drawn to reliability at scale; product and leadership tracks for the people moving Agentic AI from slide decks to business outcomes. The through-line is the same: learn fast, build faster, measure everything, iterate. Start with our best selling course: AI Coder: Complete Claude Code & Coding Agents Course - build complete products at speed with AI coding agents like Claude Code, Cursor, Copilot and Codex, no coding background required. AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents - a hands-on path from your first prompt to production patterns: 20+ models, RAG, QLoRA fine-tuning, and agents with LangChain/LangGraph. AI Engineer Agentic Track: The Complete Agent & MCP Course - design, orchestrate, and deploy robust AI agents across OpenAI Agents SDK, CrewAI, LangGraph and MCP. AI Engineer Production Track: Deploy LLMs & Agents at Scale - scaling patterns for pipelines, monitoring, and enterprise rollout on AWS with Bedrock, Google Cloud Platform, Azure and MLOps. AI Builder: Create Agents, Voice Agents & Automations in n8n - wire up low-code AI agents, voice agents and business automations in n8n with ElevenLabs, RAG and MCP. Practical Guide to AI Agents & Agentic AI with Claude Cowork - build six working no-code AI agents on your real tools (Gmail, Slack, Notion, Calendar) with Claude Cowork and MCP. AI Leader: Generative AI & Agentic AI for Leaders & Founders - a concise playbook for strategy, governance, and ROI with Generative AI and agents. If your goal is to level up quickly and ship something real, join us. Learn the concepts, touch the tools, build the thing - then take it to users. That’s the Ligency way.
All courses by Ligency →Yes — it is rated "All Level" and starts from the fundamentals, though beginners should budget extra time for the practice exercises.
Last updated 11/2026. Lifetime access means future refreshes are included at no extra cost.
With a 4.7★ average from 1,165,643 students, our Udemy course reviews put it above most Data Science alternatives.
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BestsellerBecome an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI, RAG, LoRA and AI Agents.