Developing personalize our customer journeys to increase satisfaction & loyalty of our expansion recognized by industry leaders.
Build robust, mathematically rigorous machine learning algorithms, scalable feature engineering pipelines, and resilient production prediction systems. 10 weeks of instructor-led live training, project bootcamp, and CV marketing until you are hired.
Beginner-friendly. If you are not sure whether that describes you, the consultation exists to answer exactly that — and to tell you if a different programme is the better start.
Tax included — the price shown is the price you pay. This covers the training stage. The bootcamp and placement stages are priced separately.
Live Instructor-Led
Statistical Learning
Feature Stores
Distributed ML
Model Registries
Everything covered in the program, in the order you'll cover it.
Classical methods, applied properly
Where most model quality actually comes from
Reach for networks when they earn their cost
The engineering that makes models durable
Every AVIROwork program follows a proven four-stage pathway engineered to take career switchers from zero experience through to placed UK tech professionals:
50 hours of instructor-led evening and weekend classes led by senior UK industry practitioners.
Build production-grade solutions, enterprise architectures, and pipelines that get peer reviewed.
Technical CV rewrite, LinkedIn branding, and production GitHub portfolio polish.
Direct candidate introduction to employer networks and technical interview drills until hired.
The bootcamp runs the same five stages whatever you enrolled in, so the portfolio you finish with is deep in one technology rather than shallow across several. Each is scoped, designed, built and reviewed.
A first build that puts the core concepts to work — environments configured, the basic workflows exercised, the fundamentals proven rather than assumed.
A larger solution with several components and an integration or two, applying the practices that are conventional in your stack rather than improvising.
A design-led build: scalability, monitoring and the production-grade patterns your field actually uses, decided before they are implemented.
A realistic situation with services that depend on each other, security to harden and performance to tune — the kind of work that is waiting on the other side of the offer.
End to end, everything together: planned, designed, built, deployed and documented well enough to sit at the top of your GitHub profile.
The same seven things in every programme on the site — the subject is what changes.
Taught live by a practitioner, not pre-recorded video you work through alone.
Per programme as standard — 60 for IT Support Analyst, 70 for the AI Consultant and cloud engineering tracks.
Five briefs in your own stack, each scoped, designed, built and reviewed the way a delivery team would.
One mentor who stays with you for the whole programme, rather than whoever is free that week.
Both rewritten around the work you actually built, and positioned for the roles you are targeting.
Mock interviews on the technical and the competency side, including defending the projects you built.
Your profile put in front of employers, and the search continues until you are hired.