Professional Training · Applied AI Engineering Track
Retrieval-Augmented Generation (RAG) Systems
Learn to design and operate Retrieval-Augmented Generation systems that ground LLM outputs in your own data. The course covers ingestion, chunking, embedding and retrieval strategies, plus the evaluation techniques that keep a RAG system accurate in production.
Authorised Instructors
Eric Tai
Head, Technology
- Security – Specialty
- DevOps Engineer – Professional
- Solutions Architect – Professional
- CloudOps Engineer – Associate
- +4 more
Hui Liang
Chief Digital Officer
- Security – Specialty
- Generative AI Developer – Professional
- Solutions Architect – Professional
- CloudOps Engineer – Associate
- +5 more
Marcus Low
Technical Programme Manager
- Solutions Architect – Associate
- AI Practitioner
- Cloud Practitioner
Gabriel Wong
Technical Programme Manager
- DevOps Engineer – Professional
- Generative AI Developer – Professional
- Developer – Associate
- Solutions Architect – Associate
- +2 more
Any of these AWS Authorised Instructors may deliver this class, depending on the scheduled run. Trainers confirmed on enrolment.
Who Should Attend
- Data Engineers: Engineers building ingestion pipelines for RAG systems.
- ML Engineers: Engineers tuning retrieval and generation quality.
- Backend Developers: Developers exposing RAG systems through application APIs.
- Solutions Architects: Architects designing knowledge-grounded AI systems.
- Data Scientists: Scientists evaluating retrieval and answer quality.
Prerequisites
This is an intermediate course. To get the most from it, you should have:
Working knowledge of Python.
Familiarity with vector or document databases is helpful.
Basic exposure to LLM APIs.
Learning Objectives
In this course, you will learn to:
Design ingestion pipelines: Chunk, embed and index documents for retrieval.
Tune retrieval quality: Select and evaluate embedding and re-ranking strategies.
Ground generation: Combine retrieved context with LLM prompting reliably.
Evaluate accuracy: Measure and improve answer relevance and faithfulness.
Operate in production: Monitor freshness, cost and latency of a live RAG system.
Certification
This course does not map to a vendor certification exam. It builds the practical skills behind My Code Campus’s own forward-deployed RAG work with enterprise and healthcare clients. Every participant receives a My Code Campus certificate of completion.
In-person in Kuala Lumpur or live virtual. Team & enterprise rates available.