Hands-on, cohort-based Generative AI programs for Software and DevOps Engineers — focused on building real-world AI systems, not hello-world demos.
Every program is cohort-based, hands-on, and designed for engineers who want to go beyond tools and understand how AI systems actually work.
For engineers who already understand GenAI fundamentals and want to go deeper. A hands-on, system-level course covering MCP, production-grade RAG, supervised fine-tuning, GPU inference, and model evaluation.
All timings in PST — please adjust for your timezone.
IdeaWeaver AI Labs is a hands-on learning platform built for Software Engineers and DevOps Engineers who want to transition into Generative AI by understanding how real systems work.
Here, you learn how Generative AI actually works — how models are trained, evaluated, and used in real-world systems. We start from first principles and don’t assume prior GenAI or ML knowledge. A working knowledge of Python is the only prerequisite.
You’ll work on real-world patterns and get hands-on access to real GPU resources. Built by engineers, for engineers.
Weekly live classes and hands-on exercises focused on real-world Generative AI systems — not slides, not theory dumps.
Train, fine-tune, build, and evaluate models using real GPU resources — not simulated environments or toy datasets.
Start from first principles and progress all the way to building and understanding small language models from scratch.
Learn alongside other engineers at the same stage. Live sessions, shared exercises, and a community that moves together.
Our programs are cohort-based and focused on learning by building. Instead of relying on prompt-only workflows, students work on practical exercises and mini-projects that reflect how Generative AI systems are designed, trained, evaluated, and deployed in real-world environments.
All programs emphasize practical implementation, clear mental models, and engineering depth. Students also get access to real GPU resources for hands-on experimentation and model training.
Thank You Prashant for the wonderful course. It was really helpful.
Thank you so much for this wonderful deep-dive course and looking forward for RAG deep-dive session too.
Thanks Prashant Sir, The way you explained concepts and supported us throughout the batch helped build both our understanding and confidence. 🙏
It was an incredible journey @IdeaWeaver Support — You have helped learn the basics and given the opportunity to expand our horizons. Your teaching methodology has the power to take your audience to another world. It was a great learning experience. Thank you!!
Thanks Prashant — I didn't even realize our batch was over (I came Sat morning as usual to join in and then realized 😅). Indeed all the classes were very good — your deep knowledge in each aspect (and humility to not 'hallucinate' when you didn't know something 😅) was appreciated.
I think you did a fantastic job and I learned some important things.
Founder, IdeaWeaver AI Labs
With 20+ years of experience across Software Engineering, DevOps, Cloud, Kubernetes, and Large-Scale Distributed Systems. Over the years, I’ve worked on systems used by millions of users, built and operated production-grade cloud platforms, and helped teams debug, scale, and secure complex infrastructure.
More recently, my focus has been on Generative AI — specifically how LLMs actually work under the hood and how to build reliable, real-world GenAI systems. I’m the author of multiple technical books, a CNCF Kubestronaut, RHCA, and an AWS Community Builder.
I created IdeaWeaver AI Labs to help engineers transition into Generative AI the right way — by building systems, understanding fundamentals, and learning through hands-on work, not hype.
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Read on Medium →No. We start from first principles. A working knowledge of Python is the only prerequisite. All programs are designed for Software and DevOps Engineers making the transition.
You learn alongside a group of engineers at the same stage. Sessions are live and instructor-led, typically running 3 days a week. Recordings are available for enrolled students.
Yes. All programs that require GPU compute — fine-tuning, model training, and evaluation — include access to real GPU resources, not simulated environments.
The 1-month programs (GenAI for DevOps, AI Agents, SLM) focus on a single domain. The 4-month program is a full-stack GenAI curriculum covering everything from LangChain and RAG to model internals and building small language models from scratch.
At this time we do not offer refunds. If you have questions about a program before enrolling, reach out directly.
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