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From engineer to AI architect: transformer internals, distributed training, fine tuning and alignment, advanced RAG, multi agent systems, and LLMOps at scale.
8 modules · 48 lessons
Deep learning at depth with modern architectures, training at scale and distributed systems, model customization and alignment, advanced RAG and knowledge systems, agentic AI and multi agent architecture, LLMOps and inference optimization, evaluation and governance, and a capstone production AI platform.
This is the final stage of the Ucanly Artificial Intelligence track, where engineers become AI architects. Built for developers with hands on experience training deep learning models and shipping AI features with PyTorch, transformers, and RAG, this program goes deep into transformer internals, distributed training across GPUs, full fine tuning, LoRA and QLoRA, RLHF and preference alignment, and advanced RAG architectures including graph RAG and multi hop retrieval. You will design multi agent systems with LangGraph, optimize inference with vLLM and quantization, and apply real LLMOps discipline covering evaluation, guardrails, bias, and governance. You will graduate having architected and launched a scalable, production grade AI platform with a customized model, a multi agent layer, full evaluation and observability, and an automated CI/CD pipeline.
Complete this course to earn a verified Ucanly certificate you can add to your profile, share on LinkedIn, and showcase to employers as proof of the skills you've built.
It is recommended, but hands on experience training deep learning models and shipping AI features with PyTorch, transformers, and RAG is sufficient to start.
Yes, you will run a distributed training job across multiple GPUs using techniques like mixed precision and DeepSpeed.
Full fine tuning, LoRA and QLoRA, instruction tuning and dataset engineering, and RLHF and DPO based preference alignment.
A scalable, production grade AI platform with a customized model, a multi agent layer, full evaluation and observability, and an automated CI/CD pipeline, defended in a live architecture review with Ucanly mentors.