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Build a RAG Chatbot with n8n

Course Information

  • Sessions 1 day
  • Duration 7.5 hrs
  • Level Beginner
  • Assessment NA

Venue

Kuala Lumpur: G-3A-02, Corporate Office Suite, KL Gateway, No. 2, Jalan Kerinchi, Gerbang Kerinchi Lestari, 59200 Kuala Lumpur, Malaysia

Course Brochure

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Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.

Build a RAG Chatbot with n8n

Course Code: C978

9 Review(s) | Add Your Review

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What's This Course About

Build a RAG Chatbot with n8n shows you how to create an AI chatbot that answers questions accurately from your organisation's own documents and data. Generic chatbots only know what their AI model was trained on, so they fall short when asked about your products, policies or procedures; Retrieval-Augmented Generation (RAG) solves this by retrieving relevant information from your knowledge base and giving it to the AI before it answers. The course is designed for business users, operations and IT professionals, and anyone who wants to build practical AI assistants without heavy coding.

You will start by understanding RAG chatbots, learning how embeddings, vector databases and retrieval work, how RAG reduces hallucinations, and how to prepare and organise documents such as FAQs, manuals and policies for best results. You will see where RAG chatbots add value in customer service, HR, internal help desks and sales support. Next you will build a RAG chatbot with n8n, creating workflows that load and chunk documents, generate embeddings, store them in a vector database and connect an AI agent that retrieves the right information to answer questions.

Throughout the course you will also learn how to test and improve answer quality, add memory and source citations, embed the chatbot in a website or chat app and keep data secure. Every step is hands-on in n8n. By the end, you will be able to build, deploy and maintain a RAG chatbot that gives accurate, trustworthy answers grounded in your own knowledge.

Why Take This Course?

  • Hands-On Learning Learn by doing. Every topic is practised hands-on, so you leave with skills you can use at work straight away.
  • Live Coaching Experienced instructors coach you live, answer your questions and guide you step by step.
  • Free Post-Course Consultation Stuck after class? Message your trainer any time for guidance as you apply what you have learned.
  • Always-Updated Materials Materials are refreshed to stay relevant. Log in to our LMS any time to get the latest version.
HRD Corp Claimable

🏦 HRD Corp Claimable

This course is HRD Corp claimable for eligible employers. Grant approval and reimbursement remain subject to HRD Corp requirements, the employer’s available levy and the approved grant details. How the HRD Corp process works →

Course Fee

MYR1,100.00
+ 8% SST

Course Date

Course Time

Course fees are shown before SST. An 8% SST is included in the estimated total during registration.

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Disclaimer: The course dates displayed on our website are tentative and subject to trainer availability. We will confirm the final date after checking with the trainer. You are also welcome to email us your preferred date at sales@tertiarycourses.com.my, and we will do our best to coordinate with the trainer's schedule.

Post-Course Support

  • We may provide consultation related to the subject matter after the course.
  • Please email your queries to sales@tertiarycourses.com.my and we will forward your queries to the subject matter experts and get back to you as soon as possible.

Cancellation & Reschedule Policy

  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
  • Note: the venue of the training is subject to changes due to class size and availability of the classroom. The minimum class size to start a class is 3 Pax.

Course Details

Course Details

What You'll Learn

Topic 1: Understanding RAG Chatbots

Topic 2: Building a RAG Chatbot with n8n

Course Info

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

Hardware: Windows PC or Mac laptop

Job Roles

Job Roles

  • Chatbot Developer
  • Content Strategist
  • Customer Experience Manager
  • Digital Marketing Specialist
  • AI Solutions Architect
  • Technical Writer (for chatbot scripts)
  • Customer Support Manager
  • UX Designer
  • Product Manager
  • Digital Transformation Specialist
  • CRM Specialist
  • E-commerce Operations Manager
  • IT Project Manager
  • Business Analyst (focusing on customer engagement)
  • User Interface Designer (for chat interfaces)

Trainers

Trainers

Retrieval-augmented generation chatbots built in n8n are a speciality of Dr. Alfred Ang, a full-stack AI developer, Agentic AI solution architect and corporate trainer who serves as CTO of Tertiary Infotech Academy Pte Ltd in Singapore. Dr. Ang builds intelligent agents and business solutions end-to-end across front end, back end, databases, cloud deployment and native mobile apps, and has published more than 300 public repositories on GitHub. The n8n-ragdemo project is a no-code RAG demonstration in which a browser PDF uploader feeds an in-memory vector store and a Telegram AI agent powered by Google Gemini answers questions from those documents. Its sequel, n8n-ragdemo2, pairs a cooking and bakery training centre landing page with a customer-service RAG chatbot and twenty mock course brochures, closely mirroring how an organisation would put its own materials to work. A related bakery lead-magnet site deliberately uses context-stuffing with an n8n and Gemini chatbot instead of retrieval, a useful contrast for deciding when RAG is genuinely needed. Dr. Ang has also built n8n-hrportal, whose OpenAI HR chatbot is guarded so it stays on topic, digitalhuman, a voice-enabled avatar trained on an organisation's content, and the self-improving lead-generation chatbot inside the ai-cms content platform. Each project has exposed practical issues around chunking, retrieval quality, hallucination and keeping answers current. That hands-on track record means Dr. Ang can explain not only how to build a RAG chatbot, but how to keep one trustworthy.

Build a RAG Chatbot with n8n turns those lessons into a guided, hands-on build. The first topic, understanding RAG chatbots, explains why generic chatbots only know what their model was trained on, how retrieval-augmented generation grounds answers in an organisation's own documents, and how embeddings, vector stores and prompts fit together. Dr. Ang uses the context-stuffing versus retrieval comparison to show when each approach makes sense and what it costs. In the second topic, building a RAG chatbot with n8n, participants create the workflow themselves: uploading documents, splitting them into chunks, generating embeddings, storing them in a vector store, connecting an AI agent node to a language model, and exposing the chatbot through a chat interface or messaging app such as Telegram. Learners then test the bot with realistic questions, inspect which passages were retrieved, and adjust chunk sizes, prompts and guardrails until answers are accurate and stay on topic. Dr. Ang shares troubleshooting tips gathered from the chatbots described above, including how to handle questions the documents cannot answer and how to keep content up to date. The class suits business users, trainers, support teams and developers alike, as n8n's visual editor means no coding background is needed. Everyone leaves with a working chatbot built on their own content. To explore the RAG demos and chatbot projects referenced in class, visit Dr. Options for hosting, cost control and protecting sensitive documents are also discussed, so the chatbot can move safely beyond the classroom. Ang's portfolio at https://github.com/alfredang.

Review

Customer Reviews (9)

Very satisfied Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
The trainer was knowledgeable and explained the concepts clearly with real-world examples. (Posted on 21/03/2026)
Great practical training Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Good hands-on training with plenty of examples. I feel much more confident applying these skills now. (Posted on 27/10/2025)
Superb training Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Well organised course with clear objectives. The step-by-step approach made it easy to follow. (Posted on 26/04/2025)
Would attend again Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 04/11/2024)
Practical and relevant Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
The course materials were detailed and easy to reference afterwards. Great value for money. (Posted on 05/07/2024)

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