LLM Engineering
Build production apps with LLM APIs — function calling, structured output, streaming.
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After this skill you can…
- Call LLM APIs with function/tool use
- Parse structured JSON from LLM output
- Handle streaming responses
- Implement retry/fallback logic
Prerequisites
Watch (10 videos)
Build an LLM and RAG-based Chat Application using AlloyDB and LangChain
→ Build an LLM-based chat application→ Deploy a RAG pipeline with LangChain
FULLY LOCAL Mistral AI PDF Processing [Hands-on Tutorial]
→ Build a local AI-powered PDF processing engine→ Use faiss and sentence transformers for information retrieval
Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation
→ Build a Multimodal Vision Language Model from scratch→ Implement contrastive learning using CLIP and SigLip
Ultimate Guide: Deploy Google ADK Agents to Vertex AI & Cloud Run (Step-by-Step Tutorial)
→ Deploy AI agents to cloud environments→ Use Vertex AI and Cloud Run for scalable deployment
How to Make an Asteroids Game Bot (LIVE)
→ Develop AI-powered game bots→ Apply Neuroevolution to game development
Using Claude Code + Nano Banana Pro To Create a Dataset of Engineering Drawings
→ Design and implement LLM-based engineering solutions→ Integrate LLMs with CAD tools
End to End LLMs with Azure
→ Deploy LLMs with Azure OpenAI Service→ Implement RAG with Azure Search
Chain-of-Agents: Multi-Agent Distillation for LLM Problem-Solving - Paper Overview
→ Implement Chain-of-Agents for LLMs→ Train LLMs with multi-agent distillation
Build Multi-Modal Applications with LlamaIndex and Claude 3.
→ Build a multi-modal application with LlamaIndex→ Integrate Claude 3 with LlamaIndex
Livestream: From Data to Deployment Building European AI at Scale
→ Train large-scale AI models→ Deploy AI models at scale
Read (10 articles)
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