Systems-First. Hardware-Aware.
Production-Oriented.

Technical programmes for engineering teams who need to understand AI systems at the layer that actually matters, from hardware to production.

Practical, systems-first, production-oriented

Built around real production constraints
No toy examples — every exercise maps to a live system
Outcome: engineers who can ship, not just prototype
How We Teach

Our Training Modules.

Tensor Cores & CUTLASS

Tensor Cores & CUTLASS

How GPU matrix multiply units work, when they saturate, and how to keep them fed. The foundation of every high-performance inference kernel.

GPUCUTLASSMatrix MultiplyKernels
Attention Mechanisms

Attention Mechanisms

Flash Attention, multi-query, grouped-query — the architectural decisions that determine memory footprint and latency at scale.

Flash AttentionMulti-QueryMemoryLatency
eBPF & System Profiling

eBPF & System Profiling

Kernel-level observability without instrumentation overhead. Cross-domain CPU–GPU profiling of production systems in real time.

eBPFProfilingObservabilityCPU-GPU
Non Blocking Hash Map

Non Blocking Hash Map

Lock-free hash tables, atomic operations, and the concurrency patterns that make distributed systems fast under real workloads.

Lock-FreeWarp PrimitivesConcurrencyPerformance
Concurrent Skip List

Concurrent Skip List

Probabilistic data structures for sorted concurrent operations. O(log n) search, insertion, and deletion without the complexity of balanced trees.

CUDAMemory HierarchyBandwidthExecution Model
Programs

Five Training Programs.

Five technical programs. Each one grounded in production reality — not academic abstraction.

System Architecture for AI
01

System Architecture for AI

How production AI systems are actually built — from hardware selection to serving topology.

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Design & Development of LLMs
02

Design & Development of LLMs

Architecture decisions that determine whether a model survives in production.

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System Optimization for LLMs
03

System Optimization for LLMs

Kernel-level profiling, memory hierarchy, quantisation — where real performance gains live.

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Foundations of Deep Learning
04

Foundations of Deep Learning

The mathematical and systems foundations required to reason about modern deep learning.

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Introduction to ML, DL and NLP
05

Introduction to ML, DL and NLP

A rigorous introduction to machine learning for technical professionals.

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Delivery

Seminar. Deep Dive.
Private Workshop.

Three formats. Each one designed for a different level of depth and a different audience.

Seminar

Leadership & strategy

A focused session for CTOs, VPs, and technical leads. Strategic framing of AI infrastructure decisions with Q&A.

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Deep Dive

Engineering teams

Hands-on technical program. Engineers leave with working implementations and a methodology they can apply immediately.

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Private Workshop

Entire org

Fully customised to your stack, your team, and your production environment. Delivered on-site or remote.

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Get Started

Organise a Seminar.

Every training engagement starts with a conversation about your team, your stack, and what you need to understand. We scope from there.

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