Developing personalize our customer journeys to increase satisfaction & loyalty of our expansion recognized by industry leaders.
Master the complete machine learning lifecycle, from advanced statistical modelling and deep learning to automated MLOps pipelines and cloud deployment. 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.
GST 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
Scikit-Learn
PyTorch Core
MLflow Tracking
Kubernetes MLOps
Everything covered in the program, in the order you'll cover it.
The half data scientists usually lack
Train models bigger than one machine
The pipelines models actually depend on
Own it once it is live
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.