Technical Guides
Step-by-step walkthroughs for real engineering tasks
Detailed guides covering environment setup, building production AI systems, deploying models, and everything in between — written for engineers who want depth, not summaries.
beginner
45 min
Complete AI Development Environment Setup
Set up a professional AI engineering workspace from scratch — Python, VS Code, Jupyter, virtual environments, and your first Groq API call.
pythonvscodejupytersetup
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advanced
75 min
Deploying ML Models to Production
A complete playbook for taking a trained model from your laptop to a production API — serialisation, FastAPI, Docker, monitoring, and CI/CD.
Prerequisites
pythonbasic-ml-knowledgedocker-basics
mlopsfastapidockerdeployment
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advanced
90 min
Build a Production RAG Pipeline From Scratch
Go from zero to a production-ready Retrieval-Augmented Generation system — chunking, embeddings, vector search, reranking, and evaluation.
Prerequisites
pythonbasic-llm-knowledge
ragembeddingsvector-searchproduction
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