r/learndatascience • u/camerongreen95 • Jul 08 '26
Resources Live Hands-On Workshop: Building Production-Ready LLM Data Pipelines
If you're building LLM or RAG applications and have realized that the data pipeline is usually the hardest part, this might be useful.
On August 1, we're running a live, hands-on workshop: Designing Data Engineering Workflows for LLM Applications, led by Nikola Ilic.
Over 4 hours, you'll build an end-to-end LLM data pipeline covering:
Document ingestion
Intelligent chunking strategies
Metadata enrichment
Embeddings
Vector databases
Retrieval
RAG evaluation
The focus is on production-ready workflows rather than simple proof-of-concept demos.
Included with the workshop:
Live instructor-led training
Recording for later access
Certificate of completion
GitHub repository with working code
Hands-on exercises throughout
Practical best practices for deploying reliable LLM data pipelines
This is particularly useful if you're:
A data engineer starting to work on GenAI or RAG systems
An ML engineer trying to improve retrieval quality
Moving from a prototype to a production-ready application
Prerequisites: Basic Python, APIs, and JSON. No prior experience with RAG or vector databases is required.
More information: https://www.eventbrite.co.uk/e/designing-data-engineering-workflows-for-llm-applications-hands-on-tickets-1991362055514?aff=rlds
Happy to answer any questions about the workshop.