Practical AI, automation, and C++ courses — from focused lessons to full programmes — built by the engineers who ship AI to Fortune 500 companies.
Everything you need to go from curious to capable — fast.
Every course is designed by engineers who ship AI to Fortune 500 companies — not academics.
Practical labs and real-world projects from day one. No filler, no theory-only modules.
Cohort programmes include weekly office hours and direct Slack access to Velmio engineers.
Structured paths from beginner to advanced practitioner, with a clear outcome at each stage.
Build production-grade systems — LLM pipelines, C++ inference engines, AI agents.
The same curriculum used to onboard engineering teams at scale across regulated industries.
28 courses available — filter by track or sort by price.
Write prompts that actually deliver. This hands-on session covers the principles behind reliable prompting — chain-of-thought, few-shot examples, role framing, and output control — using ChatGPT, Claude, and Gemini. No coding required.
A practical walkthrough of the AI tools that operations, logistics, and project teams are using to cut admin time by 60%+. We cover document processing, meeting summarisation, workflow automation, and reporting — with live demos.
Built for lawyers and legal ops teams. Learn to use AI for contract review, clause extraction, risk flagging, and research — with a clear framework for what AI can and cannot do reliably in legal contexts.
Apply AI to the work financial analysts actually do: earnings report summarisation, sentiment analysis of filings, anomaly detection in datasets, and building AI-assisted models in Python and Excel. Comes with downloadable templates.
Build a working AI assistant that answers questions from your company's own documents. We use the OpenAI API, LangChain, and a vector database to create a private, enterprise-ready knowledge bot — deployed and tested by the end of the course.
End-to-end workflow automation using Make.com, n8n, and the OpenAI API. You'll build real automations: lead enrichment pipelines, automated email drafting, report generation, and Slack integrations — no backend infrastructure needed.
Go beyond the playground. This course covers everything between calling an LLM API and running a production-grade system: structured outputs, tool use, evals, cost management, latency optimisation, and deployment on AWS Lambda and Vercel.
The definitive course on Retrieval-Augmented Generation. You'll design, build, and evaluate a production RAG system from the ground up — covering chunking strategies, embedding models, reranking, hybrid search, and hallucination reduction.
Train and deploy your own domain-adapted language model. Covers supervised fine-tuning, LoRA, QLoRA, dataset preparation, training on consumer GPUs, evaluation with benchmarks, and serving with vLLM and HuggingFace Inference Endpoints.
Design AI systems that are fast, reliable, and cost-efficient at scale. Covers distributed inference, model serving architectures, streaming pipelines, observability, A/B testing, and the design patterns used at companies running millions of AI calls per day.
Get productive with n8n in a single session. We cover the visual workflow builder, triggers, credentials, error handling, and how to connect your first five services — from CRM to Slack to email — without writing a line of code.
Learn how to automate repetitive business tasks using AI — lead enrichment, email drafting, invoice processing, and reporting. We use n8n and the OpenAI API to build automations you can deploy the same day.
Build autonomous AI agents that reason, use tools, and execute multi-step workflows. Covers n8n's AI nodes, LangChain integration, vector memory, and connecting agents to real business systems like CRMs and databases.
Automate your entire sales pipeline — from lead capture and enrichment to follow-ups and CRM updates. Build workflows that connect HubSpot, Salesforce, LinkedIn, email, and Slack into a single automated system.
Scale n8n from side project to production infrastructure. Covers self-hosting, environment management, version control with Git, custom nodes in TypeScript, performance tuning, monitoring, and building an automation agency workflow library.
Master the new wave of AI agent frameworks. Build agents with LangGraph, CrewAI, and the Model Context Protocol (MCP). Learn tool integration, memory management, multi-agent orchestration, and deployment patterns used by top AI teams.
A practical introduction to modern C++ for engineers coming from Python, Java, or other languages. Covers the essential features of C++17 and C++20 — smart pointers, move semantics, lambdas, structured bindings, and concepts — with hands-on exercises throughout.
Write C++ that's genuinely fast. This course covers profiling with perf and Valgrind, cache-aware data structures, SIMD intrinsics, lock-free concurrency, and compiler optimisations. Every technique is benchmarked before and after.
Bridge the gap between Python ML models and production C++ runtimes. You'll integrate libtorch (C++ API for PyTorch), write custom ONNX Runtime operators, and build a C++ inference server that serves predictions at sub-millisecond latency.
Build a production AI inference engine from scratch in C++. Covers operator implementation, memory layout, quantisation (INT8/FP16), batching strategies, CUDA kernel integration, and deployment as a shared library consumed by Python runtimes.
Production systems programming for engineers who need to go deep. Topics include memory allocators, network I/O with io_uring, lock-free queues, coroutines (C++20), inter-process communication, and writing safe, testable systems code with AddressSanitizer and fuzzing.
The course for engineers building the infrastructure that ML runs on. Covers distributed training communication (NCCL, MPI), custom CUDA kernels for attention and matmul, model parallelism strategies, and building a parameter server in C++. Used by engineers at ML infrastructure teams.
End-to-end ML: from raw data to deployed model. Live sessions twice a week, mentoring from Velmio engineers, and a real-world capstone project that goes in your portfolio.
Build production RAG systems, fine-tune LLMs, and deploy AI agents that don't hallucinate. Live instruction from the same engineers who ship AI to enterprise clients.
Build the data pipelines and feature stores that AI actually needs. Most models fail not because of the model — but because of the data infrastructure beneath it.
From practitioner to AI engineer in 12 weeks. Daily live instruction, 1-on-1 mentoring, a project portfolio of three production-grade AI systems, and dedicated career support from our hiring network.
Custom AI training delivered live for your team — online or on-site. Your curriculum, your pace, your use cases. Includes a team progress dashboard and corporate certificate.
A bespoke board-level programme on AI strategy, governance, vendor management, and AI literacy. Delivered by Velmio's leadership faculty in a private executive cohort of up to 12 participants.
Self-paced, live, or team training — pick the format that fits how you learn best.
One-time payment
Full course access on your timeline. Study when it suits you, finish at your own pace.
One-time payment
Study alongside a cohort with weekly sessions run by the Velmio engineering team.
Custom
Private training for engineering teams — scoped to your stack, delivered by Velmio engineers.
Follow a structured path from first lesson to advanced practitioner. Each path is designed by the engineers who run Velmio's client projects.
Start with focused lessons, build momentum with mini-courses, graduate to a full course.
From modern C++ foundations through to building AI inference engines in production.
From no-code automations to production AI agents — master n8n and the modern automation stack.
Live cohort training with mentoring from Velmio engineers — for serious career acceleration.
Book a free 45-minute call — we'll map you to the right path based on your goals, role, and timeline.