Master LLM apps, RAG, LangGraph, AI agents, local models, and real-world projects in 2026.
LangChain adoption grew 60% YoY in 2025, powering RAG, multi-agent systems, and local LLM apps (Gartner, 2025). This data-driven ranked list of the 10 best-selling LangChain courses on Udemy uses real-time enrollments, 4.5+ ratings, 2025 curriculum updates. All courses include:
- Lifetime access
- Udemy Certificate (LinkedIn-ready)
- Hands-on projects
- 90% off sales ($10–$20)
We analyzed 40+ LangChain courses on Udemy using enrollment data, student reviews, update frequency, and 2026 relevance (LangGraph, LangSmith, Ollama, MCP).
1. ChatGPT and LangChain: The Complete Developer’s Masterclass by Stephen Grider
About This Course
This course is the #1 LangChain bestseller on Udemy, with over 10,000 students and a 4.6/5 rating from 1,500+ reviews. Taught by Stephen Grider (Udemy legend with 1M+ students across React, Docker, and Node.js, known for production-grade code and real-world deployment), it’s designed for developers who want to build scalable LLM apps without fluff. The curriculum evolves rapidly—4 major updates in 2025—covering everything from chains to 2026 trends like LangGraph workflows and streaming responses. Students rave about the active Q&A (answers in <4 hours), GitHub repos, and real projects (e.g., AI research agent, document Q&A bot). Reddit threads (r/LangChain, r/MachineLearning) call it “the gold standard for production LangChain,” with Medium reviews highlighting how it helped 75% of learners deploy apps in under a month. Unique value: Integrates Pinecone v2, Chroma, and tool calling for 2026 agentic AI. Over 80% of students report building deployable apps within 2 weeks, making it ideal for job seekers targeting AI engineer roles at $120K+ salaries. The course includes full-stack deployment with FastAPI, Docker, and AWS Lambda, plus monitoring with LangSmith—skills directly applicable to enterprise AI pipelines.
Latest Updates (2025)
- June 2025: Added LangGraph, multi-agent systems, and streaming with FastAPI.
- March 2025: Re-recorded RAG modules with hybrid search and Pinecone v2.
- Jan 2025: 3+ hours on LangSmith debugging and performance monitoring.
What You’ll Learn
- LangChain architecture: Chains, memory, callbacks, output parsers.
- Advanced RAG: Embeddings, vector DBs (Pinecone, Chroma), retrieval strategies.
- Agents & Tools: Function calling, ReAct, custom tools, multi-agent collaboration.
- Production deployment: FastAPI, Docker, AWS Lambda, monitoring.
- 2026-Relevant Skills: LangGraph state machines, local LLMs, streaming UIs.
Pros & Cons
| Pros | Cons |
|---|---|
| Production-ready code with GitHub repos – deploy on day 1. | Assumes intermediate Python; not for absolute beginners. |
| Constant updates (4x in 2025) – covers LangGraph, LangSmith. | Less focus on no-code or business use cases. |
| High engagement with assignments and real datasets. | 15 hours may feel dense for quick learners. |
| Active Q&A, community Slack, and job-ready projects. |
- Enrollment: 10,000+ students
- Rating: 4.6/5
- Duration: 15 hours
- Last Updated: June 2025
- Best for: Developers building production LLM apps
Enroll Now: ChatGPT and LangChain Masterclass (10K+ Students, Production Focus) →
Want to master RAG? → Top 10 Best Generative AI Courses on Udemy
2. Ultimate RAG Bootcamp Using Langchain,LangGraph & Langsmith by Krish Naik
About This Course
Krish Naik’s RAG-focused masterpiece has 2,000+ enrollments and a 4.7/5 rating. With 1.5M+ YouTube subscribers and real-world ML experience at iNeuron, Krish delivers enterprise-grade RAG pipelines. The course was fully refreshed in 2025 with multimodal RAG and adaptive retrieval. Students on LinkedIn report using the projects for job interviews at FAANG-level AI roles. Unique 2026 edge: Covers LangSmith tracing, hybrid search, and cost optimization for production RAG. Over 70% of graduates build RAG systems that outperform naive retrieval by 40% in accuracy, using real datasets like PDFs, web pages, and SQL databases. The course includes evaluation frameworks (RAGAS, DeepEval) and A/B testing—critical for data scientists in 2026.
Latest Updates (2025)
- July 2025: Multimodal RAG with CLIP + LLaVA.
- April 2025: LangGraph for dynamic retrieval routing.
- Feb 2025: LangSmith enterprise debugging.
What You’ll Learn
- Chunking strategies, metadata filtering, hybrid search.
- Advanced RAG: Parent-document, hypothetical questions, compression.
- LangGraph for multi-step retrieval workflows.
- LangSmith: Tracing, evaluation, A/B testing.
- Deployment: Streamlit, FastAPI, cost monitoring.
Pros & Cons
| Pros | Cons |
|---|---|
| Deepest RAG coverage on Udemy – production pipelines. | 28 hours long – not for quick learners. |
| Real datasets (PDFs, web, SQL) + evaluation metrics. | Python-heavy; less JS focus. |
| LangSmith mastery for debugging at scale. | Requires basic ML knowledge. |
| Job-ready projects with performance benchmarks. |
- Enrollment: 2,000+
- Rating: 4.7/5
- Duration: 28 hours
- Last Updated: July 2025
- Best for: RAG specialists, data scientists
Enroll Now: Ultimate RAG Bootcamp (Deepest RAG Training) →
3. LangChain- Develop AI Agents with LangChain & LangGraph by Eden Marco
About This Course
Eden Marco’s agent-building bootcamp has 5,000+ students and 4.6/5 rating. With a background in AI startups and LangChain core contributor status, Eden teaches LangGraph from the source. The course includes 10+ agent projects (e.g., travel planner, code reviewer). 2025 updates added multi-agent collaboration and human-in-the-loop. Reddit users call it “the fastest way to build autonomous agents.” Over 85% of students complete a working agent in under 10 hours, with real-world use cases like customer support bots and data analysis agents. The course emphasizes state management, memory, and reflection—core to 2026 agentic AI systems.
Latest Updates (2025)
- Aug 2025: Multi-agent systems with crewAI integration.
- May 2025: LangGraph persistence and streaming.
What You’ll Learn
- Agent types: ReAct, Plan-and-Execute, Toolformer.
- LangGraph: Nodes, edges, state management.
- Custom tools, memory, reflection.
- Deployment with Vercel, AWS.
Pros & Cons
| Pros | Cons |
|---|---|
| Fastest path to working agents (10 hours). | Less RAG depth than #2. |
| LangGraph taught by core contributor. | Focuses on agents, not full LangChain. |
| 10+ real projects with code templates. | Assumes Python basics. |
| Human-in-the-loop and reflection patterns. |
- Enrollment: 5,000+
- Rating: 4.6/5
- Duration: 10 hours
- Last Updated: Aug 2025
- Best for: Agent builders, automation
Enroll Now: AI Agents with LangGraph →
4. LLM & Generative AI Masterclass: Langchain, HuggingFace by Ankit Mistri
About This Course
Ankit’s open-source LLM course has 8,000+ enrollments and 4.7/5 rating. Focuses on HuggingFace + LangChain for local models. 2025 updates include Ollama, Llama 3, Gradio. Ideal for privacy-conscious devs. Students build full NLP pipelines with structured outputs, fine-tuning, and deployment. Over 60% of learners run models locally, avoiding API costs. The course bridges open-source and LangChain ecosystems, teaching prompt engineering, RAG, and Gradio UIs for production-ready apps. Unique value: Covers quantization, PEFT fine-tuning, and inference optimization for edge devices—key for 2026 on-device AI.
Latest Updates (2025)
- Sep 2025: Ollama + Llama 3 integration, quantization techniques.
What You’ll Learn
- HuggingFace Transformers: Pipelines, tokenizers, models.
- LangChain integration: Chains, agents, memory with open-source LLMs.
- Local RAG: Embeddings (Sentence Transformers), vector stores (FAISS, Chroma).
- Fine-tuning: LoRA, PEFT, quantization (bitsandbytes).
- Deployment: Gradio interfaces, Streamlit dashboards, API endpoints.
- Advanced: Structured outputs, JSON mode, multimodal (vision-language models).
Pros & Cons
| Pros | Cons |
|---|---|
| Comprehensive open-source stack – no API costs. | Can overwhelm absolute beginners with setup. |
| Local model focus with Ollama/Llama 3. | Less emphasis on cloud/enterprise tools. |
| Gradio/Streamlit UIs for instant demos. | Heavy on HuggingFace ecosystem. |
| Fine-tuning & quantization for edge devices. | Requires GPU for best experience. |
- Enrollment: 8,000+
- Rating: 4.7/5
- Duration: 19 hours
- Last Updated: Sep 2025
- Best for: Open-source AI, privacy-focused devs
5. Master Langchain and Ollama - Chatbot, RAG and AI Agents by Laxmi Kant
About This Course
Perfect 5.0/5 rating with 1,000+ students. Focuses on local LLMs with Ollama. Includes AWS deployment and MySQL integration. Students build privacy-first chatbots, RAG systems, and agents without OpenAI costs. The course covers custom tool creation, SQL querying, and AWS deployment for production. Over 90% of learners run full apps on personal machines, ideal for indie hackers and enterprises with data privacy needs. 2026 edge: Integrates Ollama web UI, model merging, and hardware acceleration.
Latest Updates (2025)
- Oct 2025: Agentic RAG with local models, model merging.
What You’ll Learn
- Ollama setup: Model download, quantization, GPU acceleration.
- LangChain with local LLMs: Chains, prompts, output parsers.
- RAG pipelines: PDF/web ingestion, embeddings, retrieval.
- AI Agents: Tool calling, ReAct, multi-step reasoning.
- Database integration: MySQL queries, CRUD operations.
- Deployment: AWS EC2, Docker, Ollama web UI.
Pros & Cons
| Pros | Cons |
|---|---|
| 100% local – zero API costs, full privacy. | Initial Ollama setup can take time. |
| AWS deployment for scaling local models. | Performance hardware-dependent. |
| MySQL + agents for enterprise data. | Less focus on cloud-native LLMs. |
| Model merging & web UI for customization. |
- Enrollment: 1,000+
- Rating: 5.0/5
- Duration: 14 hours
- Last Updated: Oct 2025
- Best for: Local LLM devs, privacy-first apps
Enroll Now: Master Langchain and Ollama →
6. Generative AI for NodeJs: OpenAI, LangChain - TypeScript by Alex Dan
About This Course
JS/TS-focused with 1,000+ students. Covers Pinecone, real-time data, multimodal. Alex teaches full-stack GenAI in Node.js with TypeScript, including embeddings, agents, and real-time streaming. Students build production apps with Express, Pinecone, and WebSockets. The course is tailored for web developers transitioning to AI, with 2026 updates on Pinecone v3 and tool integration. Unique: Type-safe LangChain wrappers and Next.js integration.
Latest Updates (2025)
- Nov 2025: Pinecone v3, tool calling, Next.js 15 streaming.
What You’ll Learn
- LangChain.js: Chains, memory, callbacks in TypeScript.
- Vector DBs: Pinecone indexing, hybrid search.
- Real-time: WebSockets, Server-Sent Events.
- Agents: Custom tools, ReAct, multi-agent.
- Full-stack: Next.js frontend, Express backend.
- Multimodal: Image generation, vision models.
Pros & Cons
| Pros | Cons |
|---|---|
| Full TypeScript – production-grade safety. | Node.js only; no Python. |
| Real-time streaming with Next.js. | Assumes JS/TS experience. |
| Pinecone v3 + serverless deployment. | Less open-source model focus. |
| Web dev friendly transition to AI. |
- Enrollment: 1,000+
- Rating: 4.6/5
- Duration: 12 hours
- Last Updated: Nov 2025
- Best for: JS/TS devs, full-stack AI
Enroll Now: GenAI for NodeJs →
7. Generative AI on AWS - Amazon Bedrock, RAG & Langchain by Rahul Trisal
About This Course
AWS-centric with 3,000+ students. Includes 9+ use cases, Streamlit apps. Rahul covers Bedrock, RAG, agents, and no-code basics. Students build enterprise apps with AWS services, ideal for cloud engineers. The course includes MCP, multi-model routing, and cost optimization for 2026 cloud AI. Unique: Bedrock Guardrails, knowledge bases, and Lambda integrations.
Latest Updates (2025)
- Oct 2025: MCP, multi-model routing, Guardrails.
What You’ll Learn
- Amazon Bedrock: Claude, Llama, Titan models.
- RAG with Knowledge Bases, OpenSearch.
- LangChain on AWS: Chains, agents, memory.
- No-code: PartyRock, Streamlit on ECS.
- Security: IAM, Guardrails, encryption.
- Cost optimization: Provisioned throughput, monitoring.
Pros & Cons
| Pros | Cons |
|---|---|
| Enterprise AWS depth with Bedrock. | Requires AWS account & costs. |
| 9+ real-world use cases. | Less local/offline focus. |
| No-code + code paths. | AWS-specific; not multi-cloud. |
| Guardrails & compliance ready. |
- Enrollment: 3,000+
- Rating: 4.5/5
- Duration: 16 hours
- Last Updated: Oct 2025
- Best for: Cloud AI, AWS engineers
8. Generative AI for Javascript Developers - LangChain, RAG by Amit Gupta
About This Course
JS RAG focus with 2,000+ students. Embeddings, vector DBs in Node. Amit teaches RAG in JavaScript with Node.js workflows, ideal for frontend devs entering AI. The course includes real-time data, embeddings, and production deployment. 2026 updates: Supabase vector, Redis caching, edge functions.
Latest Updates (2025)
- Sep 2025: Supabase vectors, Redis hybrid search.
What You’ll Learn
- LangChain.js RAG: Ingestion, chunking, retrieval.
- Vector stores: Supabase pgvector, Redis.
- Real-time data: WebSockets, change streams.
- Edge deployment: Vercel, Cloudflare Workers.
- Frontend integration: React hooks, streaming UI.
Pros & Cons
| Pros | Cons |
|---|---|
| JS-native RAG pipelines. | Assumes Node/React basics. |
| Real-time + edge ready. | No Python/LangChain.py. |
| Supabase/Redis for modern stacks. | Less agent complexity. |
| Production deployment focus. |
- Enrollment: 2,000+
- Rating: 4.6/5
- Duration: 11 hours
- Last Updated: Sep 2025
- Best for: JS RAG, frontend AI
Enroll Now: GenAI for JS Devs →
9. AI-Agents: Automation & Business with LangChain & LLM Apps by Arnold Oberleiter
About This Course
Business automation with 4,000+ students. Multi-lang, monetization strategies. Arnold teaches agents for business use cases, including sales, marketing, and automation. The course covers Python, Node, JS, and monetization models for AI products. Unique: SaaS templates, Stripe integration, customer onboarding flows.
Latest Updates (2025)
- Nov 2025: Hybrid Python/JS stacks, Stripe billing.
What You’ll Learn
- Business agents: Lead gen, email automation, CRM sync.
- Multi-language: Python, Node.js, JavaScript.
- Function calling: APIs, databases, external tools.
- Monetization: SaaS pricing, Stripe, analytics.
- Deployment: Vercel, Render, AWS.
Pros & Cons
| Pros | Cons |
|---|---|
| Business + tech – build & sell AI products. | Less deep technical depth. |
| Multi-language support. | Broad scope may dilute focus. |
| Stripe + SaaS templates. | Not for pure developers. |
| Real monetization case studies. |
- Enrollment: 4,000+
- Rating: 4.5/5
- Duration: 13 hours
- Last Updated: Nov 2025
- Best for: Business automation, AI entrepreneurs
Enroll Now: AI-Agents Automation →
10. Langchain for beginners : Build GenAI LLM Apps in Easy Steps by Bharath Thippireddy
About This Course
Beginner-friendly with 1,000+ students. Streamlit apps, open-source models. Bharath guides absolute beginners through LangChain with simple projects, Streamlit UIs, and open-source models. The course builds confidence with step-by-step instructions, ideal for non-coders entering AI. 2026 focus: No-code agents, visual debugging.
Latest Updates (2025)
- Oct 2025: Streamlit multi-page apps, no-code agents.
What You’ll Learn
- LangChain basics: Prompts, chains, memory.
- Simple RAG: PDF upload, Q&A chatbot.
- Agents: Basic tools, web search.
- UI: Streamlit dashboards, file upload.
- Open-source models: Ollama basics.
- Deployment: Streamlit Community Cloud.
Pros & Cons
| Pros | Cons |
|---|---|
| Zero coding barrier – visual + code. | No advanced RAG/agents. |
| Streamlit for instant apps. | Light on production scaling. |
| Open-source + free deployment. | Not for experienced devs. |
| Confidence-building projects. |
- Enrollment: 1,000+
- Rating: 4.6/5
- Duration: 8 hours
- Last Updated: Oct 2025
- Best for: Newcomers, no-code entry
Enroll Now: LangChain for Beginners →
Detailed Comparison Table: Top 10 LangChain Courses on Udemy 2026
| Rank | Course Title | Enrollments | Rating | Hours | Last Update | Sale Price | Certificate | Best For | Link |
|---|---|---|---|---|---|---|---|---|---|
| 1 | ChatGPT and LangChain (Grider) | 10K+ | 4.6 | 15 | Jun 2025 | $12.99 | Yes | Production Apps | Enroll |
| 2 | Ultimate RAG Bootcamp (Naik) | 2K+ | 4.7 | 28 | Jul 2025 | $14.99 | Yes | RAG Mastery | Enroll |
| 3 | Develop AI Agents (Marco) | 5K+ | 4.6 | 10 | Aug 2025 | $11.99 | Yes | Agents & LangGraph | Enroll |
| 4 | LLM Masterclass (Mistri) | 8K+ | 4.7 | 19 | Sep 2025 | $13.99 | Yes | HuggingFace | Enroll |
| 5 | Master Langchain Ollama (Kant) | 1K+ | 5.0 | 14 | Oct 2025 | $12.99 | Yes | Local LLMs | Enroll |
| 6 | GenAI NodeJs (Dan) | 1K+ | 4.6 | 12 | Nov 2025 | $11.99 | Yes | JS/TS Devs | Enroll |
| 7 | GenAI AWS Bedrock (Trisal) | 3K+ | 4.5 | 16 | Oct 2025 | $13.99 | Yes | Cloud & Bedrock | Enroll |
| 8 | GenAI JS Devs (Gupta) | 2K+ | 4.6 | 11 | Sep 2025 | $11.99 | Yes | Javascript RAG | Enroll |
| 9 | AI-Agents Automation (Oberleiter) | 4K+ | 4.5 | 13 | Nov 2025 | $12.99 | Yes | Business Automation | Enroll |
| 10 | Langchain Beginners (Thippireddy) | 1K+ | 4.6 | 8 | Oct 2025 | $10.99 | Yes | Newcomers | Enroll |
How to Choose Your Perfect LangChain Course in 2026
| Your Goal | Recommended Course | Why |
|---|---|---|
| Beginner | #10 Thippireddy | 8 hours, simple projects |
| RAG Expert | #2 Krish Naik | Deepest retrieval pipelines |
| Production Dev | #1 Stephen Grider | Deployable apps, GitHub |
| JS/TS Dev | #6 Alex Dan | TypeScript, Node.js |
| Local LLMs | #5 Laxmi Kant | Ollama, privacy |
| Business Automation | #9 Arnold | Monetization, sales |
Pro Tip: Use coupon UDEAFFHP22026 → 85% off all courses.
FAQs: Everything About Udemy LangChain Courses 2026
Q: What is the best LangChain course for beginners on Udemy in 2026?
A: Bharath Thippireddy’s Langchain for beginners stands out for newcomers with its easy steps to build GenAI LLM apps. For a broader intro, Stephen Grider’s ChatGPT and LangChain Masterclass adds production-ready projects.
Q: How much do Udemy LangChain courses cost?
A: Most courses are priced between $10-$20 during frequent Udemy sales. Regular prices range from $80-$150, but with coupon UDEAFFHP22026, you can get up to 85% off.
Q: Do these courses provide certificates?
A: Yes, all recommended Udemy courses provide a certificate of completion that you can add to your LinkedIn profile or resume.
Q: How long does it take to complete a LangChain course?
A: Most comprehensive LangChain courses take 8-28 hours. At 3-5 hours per week, finish in 1-3 weeks while building RAG and agent skills.
Q: Which LangChain course is best for developers or business owners?
A: Developers: Alex Dan’s Generative AI for NodeJs. Business owners: Arnold Oberleiter’s AI-Agents for automation and monetization.
Q: How do these courses prepare me for generative AI careers?
A: Cover RAG, agents, LangGraph, LangSmith, and real-world projects—essential for AI engineer or LLM developer roles in 2026 ($120K+ avg).
Q: Can I get a refund?
A: Yes, Udemy offers a 30-day money-back guarantee.
About the Author
CoursesWyn Team – 5+ years reviewing 1,000+ Udemy courses. We test, enroll, and rank based on real data.
Disclosure: Affiliate links. We earn commission at no cost to you. Data accurate as of November 17, 2025. Prices fluctuate.
Stephen Grider’s Masterclass tops 2026—enroll now and build production LLM apps!