JAX: XLA, Pallas & Custom Backends

Linux kernel for sys engs

This learning plan bridges the gap between traditional systems engineering and kernel-level expertise, equipping infrastructure professionals with the deep technical knowledge needed to optimize, debug, and customize Linux systems at scale. It's ideal for systems engineers, SREs, and infrastructure architects who need to go beyond surface-level Linux administration to solve complex performance issues, implement custom kernel modifications, or manage large-scale production environments where kernel behavior directly impacts reliability and efficiency.

Transformers

This learning plan is essential for developers and tech enthusiasts looking to master the technology driving the current AI boom. It bridges the gap between theoretical neural networks and practical implementation of state-of-the-art Large Language Models.

LLM personalization and memory

This learning plan is essential for AI engineers, ML practitioners, and developers who want to move beyond basic LLM usage to create truly intelligent, personalized applications. As businesses demand AI systems that understand context, remember user preferences, and adapt over time, the ability to implement memory systems and personalization techniques has become a critical competitive advantage in the AI space.

machine learning

This learning plan is essential for aspiring data scientists and engineers looking to master the full lifecycle of AI development. It bridges the gap between foundational theory and production-ready deployment, making it ideal for professionals transitioning into machine learning roles.

Master AI Efficiency and Effectiveness

This learning plan is essential for professionals and leaders aiming to stay competitive in an increasingly automated economy. It provides a comprehensive roadmap from foundational theory to building advanced autonomous systems, making it ideal for anyone looking to lead digital transformation.

Excel in AI UX design talks & publications

This learning plan is essential for product designers and UX professionals working in AI who want to elevate their impact beyond execution to thought leadership. As AI transforms product design, there's growing demand for professionals who can not only build ethical, user-centered AI products but also communicate their work persuasively to diverse audiences and contribute to academic discourse. This goal serves designers aspiring to speak at conferences, serve on design juries, publish research, and shape the future of AI-powered product design.

backend coding

This learning plan provides a comprehensive roadmap for mastering the full lifecycle of backend engineering, from writing clean code to managing cloud infrastructure. It is ideal for aspiring developers and engineers looking to transition into senior roles by learning to design and deploy scalable, production-grade systems.

Master AI: LLMs, RAG & Prompt Engineering

This learning plan is essential for developers and tech enthusiasts looking to bridge the gap between basic AI usage and professional system design. It provides the technical depth needed to build robust, data-driven applications using the latest LLM and RAG frameworks.