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Course Details
Course Details
What You'll Learn
Topic 1: Understanding RAG Chatbots
- What is Retrieval-Augmented Generation (RAG) and Why Chatbots Need It
- How RAG Works: Embeddings, Vector Stores and Retrieval
- RAG Chatbot Use Cases: Customer Support, Internal Knowledge and FAQs
- Introduction to n8n: Workflows, Nodes and AI Agent Components
- Designing a RAG Chatbot: Knowledge Sources, Chunking and Prompts
Topic 2: Building a RAG Chatbot with n8n
- Setting Up an n8n Chatbot Workflow with Chat Trigger and AI Agent
- Ingesting Your Documents into a Vector Store
- Connecting the AI Agent to Your Knowledge Base with Chat Memory
- Testing and Improving Answer Accuracy of Your RAG Chatbot
- Deploying and Embedding Your RAG Chatbot on a Website
Course Info
Prerequisite
Basic computer and file-management skills are expected. Familiarity with basic workflow concepts; basic programming and API use for developer courses will help you follow the exercises.
Software Requirement
You will need the following for this course:
- n8n Cloud – free trial
Install and test the listed software before class. Confirm the required version and account or licence access in your joining instructions. Cloud and AI services may charge subscription or usage fees.
Hardware Requirement
Bring a Windows or Mac laptop supported by the listed software, with a working keyboard and sufficient storage for course exercises.
Bring your own computer and charger, with a reliable internet connection and permission to install the required software. For live online classes, also prepare a microphone or headset.
If you need help arranging a suitable device, contact us before the class to confirm availability.
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
Dr. Muhammed Siraj is a cybersecurity specialist and academic with 15 years of experience, serving as Senior Lecturer in the Department of Informatics and Director of Graduate and Continuous Education at Academic City University in Accra. He holds a PhD in Security in Computing from Universiti Putra Malaysia, where his research focused on blockchain security, an MSc in Information and Communication Technology from Aalborg University in Denmark, and a degree from the University of Ghana. He is a licensed independent assessor with Ghana's Cyber Security Authority, holds leadership roles in national cybersecurity and privacy professional bodies, and is certified as a Certified Ethical Hacker (CEH), Computer Hacking Forensic Investigator (CHFI) and Certified Data Protection Supervisor (CDPS). Before joining Academic City, he served as Acting Director of ICT and Data Protection Supervisor at Wisconsin International University College. His expertise spans penetration testing, digital forensics, incident response, malware analysis, cryptography, cloud and IoT security, zero trust architecture, cyber threat intelligence, data protection, and governance, risk and compliance.
Dr. Siraj's research interests cover blockchain, cybersecurity, distributed computing, consensus protocols and machine learning, with published work on blockchain consensus security, smart-contract privacy preservation for sensitive records in the cloud, and new consensus mechanisms. This background gives him a distinctive perspective on artificial intelligence: as organisations adopt AI tools, agents and data-driven automation, he helps learners understand how to protect the data these systems depend on, recognise new attack surfaces, and put sound governance, privacy and access controls in place so that AI can be used safely and responsibly. In the classroom he connects technical practice with regulation, privacy and human factors, drawing on real-world security and data-protection cases to show how concepts apply in professional settings, and his experiential, hands-on teaching style has made him a trusted trainer for students and working professionals alike.
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)
- Good course materials Review by Course Participant/Trainee
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Solid content and a supportive trainer. I would definitely sign up for more courses here. (Posted on 6/18/2026)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 - Great practical training Review by Course Participant/Trainee
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Good hands-on training with plenty of examples. I feel much more confident applying these skills now. (Posted on 3/8/2026)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 course materials Review by Course Participant/Trainee
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The trainer was knowledgeable and explained the concepts clearly with real-world examples. (Posted on 2/4/2026)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 - Superb training Review by Course Participant/Trainee
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A very practical course. The trainer made a complex topic simple and enjoyable to learn. (Posted on 10/24/2025)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 - Practical and relevant Review by Course Participant/Trainee
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The course materials were detailed and easy to reference afterwards. Great value for money. (Posted on 6/11/2025)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
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