Building Language Models on AWS
AWS Skill Builder
Last updated March 3, 2026
Building Language Models on AWS is a free, six-hour course for experienced data scientists and ML engineers on training, aligning, and deploying language models, from small ones up to large, on Amazon SageMaker AI. It works through the hard parts in turn: the storage and ingestion options for processing very large amounts of text; distributed training with data-parallelism and model-parallelism libraries, and using SageMaker HyperPod to cut training time by splitting the work across more than a thousand AI accelerators; aligning a model with human feedback through reinforcement learning from human feedback (RLHF); and the optimizations that improve inference performance when a model is deployed. Alongside the text instruction and knowledge checks, video demonstrations walk through labs — from setting up SageMaker Studio to distributed training, RLHF alignment, and deploying a model such as Mixtral-8x7B — that you can run in your own AWS account.
What you'll learn
- Storage/ingestion for very large text datasets
- Distributed training (data/model parallelism) on SageMaker AI
- SageMaker HyperPod across 1,000+ accelerators
- Aligning models with human feedback (RLHF)
- Optimizing inference for deployment
- Hands-on lab demos (setup → training → alignment → deploy) in your own account
Frequently asked questions about Building Language Models on AWS
Who is Building Language Models on AWS for?
Experienced data scientists and ML engineers, comfortable with Python and language-model fundamentals, who want to train, align, and deploy LLMs on Amazon SageMaker AI.
Is Building Language Models on AWS free?
Yes — Building Language Models on AWS is completely free to take.
What are the prerequisites for Building Language Models on AWS?
More than a year of experience with natural language processing, more than a year training or tuning language models, intermediate Python, and AWS Technical Essentials. An AWS account is needed to run the labs.
Do you need to code for Building Language Models on AWS?
Yes — Building Language Models on AWS involves hands-on coding.
Why we suggest this course
A deep, end-to-end treatment of building language models — distributed training at the scale of a thousand-plus accelerators, alignment with human feedback through RLHF, and inference optimization for deployment — for engineers who already work in this area and want to do it on a managed platform. Two things worth knowing: it is genuinely advanced, assuming more than a year of NLP and language-model training experience plus working Python; and it is built by AWS around Amazon SageMaker AI, so what you build is specific to that platform, and running the labs in your own AWS account can incur AWS usage charges even though the course itself is free.