We’re glad you’re here and we’re excited to help you take the next step in your AI journey.
This program was built by the Ready Tensor team, a group of engineers, researchers, and educators who’ve spent years designing, fine-tuning, evaluating, and deploying real-world AI systems.
I’m Abhyuday Desai, Ph.D., Founder and CEO of Ready Tensor, and I’ll be guiding you through this learning experience along with our team.
Together, we’ve designed this program to teach you what modern AI teams actually do — not abstract theory, but the hands-on workflows that bring large language models to life in production environments.
In this video, you’ll hear from Abhyuday Desai (Founder & CEO, Ready Tensor) about the mission and design of the program — created to bridge the gap between LLM development and real-world deployment.
You’ll learn why becoming an LLM engineer today means mastering both model fine-tuning and cloud fluency, and how this certification equips you with both.
Modern AI applications are built on more than clever prompting — they rely on engineers who can shape and serve the intelligence behind the prompts.
That means learning how to fine-tune the brain of the system — the LLM itself — so it actually understands your domain, your data, and your users’ needs.
This certification helps you master that complete lifecycle — from adapting open-source foundation models through fine-tuning and optimization, to deploying them as reliable, scalable systems in the cloud. You’ll work with real industry tools like Hugging Face, DeepSpeed, Axolotl, SageMaker, Bedrock, and vLLM, gaining experience that mirrors what AI teams use in production today.
But building great models isn’t enough on its own. The best LLM engineers understand the infrastructure that powers them — how to train efficiently, deploy cost-effectively, and monitor performance at scale. That’s why this program also equips you with practical cloud engineering skills, ensuring you’re ready to operate confidently in real-world environments.
Our goal is to prepare you for modern AI roles — where model intelligence and cloud fluency go hand in hand.
Our research on AI hiring trends showed that 70% of job postings require cloud expertise — across AWS, GCP, Azure, or similar platforms.
That’s why this program goes beyond model training. You’ll also build the cloud skills needed to deploy, monitor, and scale LLMs in real-world environments.
Modern AI isn’t built on prompts alone - it’s built by engineers who can fine-tune and deploy the brains behind them.
This program teaches you to do exactly that: adapt, train, and operationalize large language models for real-world use.
You’ll master the full lifecycle from fine-tuning open-source models with tools like Hugging Face, DeepSpeed, and Axolotl to deploying and scaling them in the cloud with SageMaker, Bedrock, and vLLM.
Because today’s LLM engineers need more than model skills, they need cloud fluency.
You’ll learn how to train efficiently, deploy cost-effectively, and monitor performance like a production engineer.
In short, this certification prepares you for the reality of modern AI work where model intelligence and cloud infrastructure meet.
The best way to prove you can fine-tune and deploy LLMs is to actually do it... and show it.
Each capstone project in this program is designed to be portfolio-grade, something you can share with hiring managers, collaborators, or future clients.
That’s what sets this program apart: a certification backed by real, demonstrable work.
This is a self-paced program, structured across nine weeks of lessons, code walkthroughs, and project checkpoints.
Each week focuses on one part of the LLM lifecycle, with videos, hands-on exercises, and guided examples that build toward your final projects.
You’ll also get access to templates, evaluation rubrics, and real-world benchmarks used by our team in production systems.
If you haven’t already, take the Readiness Check next. It’s a quick self-assessment to ensure you’re comfortable with Python, Hugging Face, and the basics of machine learning.
And don’t forget to join our Discord community. That’s where you can connect with mentors, ask questions, and share your progress with others building alongside you.
By the end of this program, you won’t just understand how large language models work - you’ll know how to fine-tune, optimize, and deploy them confidently, using the same tools trusted by leading AI teams.
Welcome to the LLM Engineering & Deployment Certification by Ready Tensor.
Let’s get started.
