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)
LLM Quantization Explained
→ Implement quantization using Llama.cpp→ Optimize model performance using GGUF file format
NEW Claude Code Update Changes EVERYTHING!
→ Optimize AI search speed→ Implement precise permissions→ Control sub-agents
AI Just Changed Everything Multi Model Fusion Explained Game Changer in AI Race
→ Design Multi-Model Fusion Systems→ Develop More Efficient AI Models→ Improve AI Accuracy
Become an AI Engineer in 2026 | Microsoft AI Engineer Program | #Shorts| #Simplilearn
→ Design AI solutions→ Deploy AI models→ Build AI-powered products
LongCat 2.0: N-Grams Beat More Experts
→ Train large language models without proprietary hardware→ Optimize model performance using alternative training methods
Chapter 7: LLM Finetuning Explained: LoRA, PEFT & When to Fine-Tune
→ Engineer LLMs→ Optimize model architecture→ Apply LoRA and PEFT techniques
Agentic AI Projects 2026: Build AI Agents with Guardrails, Governance & Evals
→ Develop LLM models with input and output guardrails→ Integrate evaluators in LLM ops pipelines
Reward Modeling: How to Train a Reward Model for LLMs
→ Design a human-aligned assistant→ Implement RLHF for LLMs→ Optimize a reward model
What exactly is multi head latent attention?
→ Optimize LLM architecture for memory usage→ Implement MLA in LLMs
Claude: NEW AI Operating System is INSANE!
→ Build AI-powered workflows→ Integrate multiple AI agents→ Automate tasks with AI
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