"Comprehensive AI education and ongoing support — so your team doesn't just use AI, they understand it, trust it, and build on it."
Role-specific tracks from zero to advanced — every program designed around practical, real-world AI skill-building.
Designed for C-suite, founders, and senior managers who need to lead AI transformation, evaluate AI investments, and build AI-literate teams — without writing a single line of code. Covers strategy, ethics, vendor evaluation, and outcome measurement.
For product managers, designers, and analysts who work alongside AI engineers and want to make better product decisions. Learn to define AI features, write model specifications, evaluate prototypes, and avoid common AI product failure modes.
A deep technical programme for software engineers and data professionals transitioning into AI/ML roles. Covers the full ML lifecycle — from data preparation through model training, evaluation, deployment, and monitoring — with real project work throughout.
Fully bespoke training programmes designed around your specific industry, tech stack, and AI initiatives already in flight. We build custom curricula, use your actual data scenarios as examples, and deliver sessions in your environment — on-site or remote.
Three tiers of technical support — from growing startups to enterprise teams with mission-critical AI systems that cannot afford downtime.
Reliable support for startups and small teams with early-stage AI deployments that need help on-demand without committing to a full retainer.
For scale-stage companies with live AI products where fast expert response and proactive monitoring make the difference between smooth operations and costly downtime.
White-glove support for organisations with mission-critical AI infrastructure, compliance requirements, and the need for embedded technical partnership — not just ticket resolution.
Every module is designed around applied outcomes — not theory for theory's sake. Your team leaves every session able to do something they couldn't before.
Before tools, concepts. We build the mental models your team needs to think clearly about AI — what it is, what it isn't, where it fails, and how to evaluate claims. This is the base layer everything else runs on.
AI is only as good as the data it learns from. This module builds data intuition — quality, bias, labelling, distribution shift, and the relationship between data decisions and model behaviour.
Hands-on with large language models — prompt engineering, RAG pipelines, fine-tuning tradeoffs, hallucination risks, and practical integration patterns for building AI-assisted workflows and products.
What happens after deployment? Model drift, retraining cadences, monitoring dashboards, incident response, and the operational discipline that keeps AI systems performing reliably in the real world.
Not a compliance checkbox — a practical module on building AI that's fair, explainable, and trustworthy. Covers bias auditing, model interpretability, regulatory landscape, and ethical decision frameworks for AI teams.
Every technical track ends with a capstone project where participants build a working AI system — either a standalone model, an LLM-powered tool, or an integration with existing systems — and present it for peer review.
Every system we build ships with comprehensive technical docs — architecture diagrams, API references, runbooks, and onboarding guides your future team can actually use.
Recorded walkthroughs of every system component — so your team can re-watch how things work long after the project ends, and onboard new members without starting from scratch.
Structured knowledge transfer sessions with your technical team — live walkthroughs, Q&A, and guided practice until your team feels genuinely confident operating the system independently.
All training clients get 12-month access to the Cogniv AI Learning Portal — a growing library of AI courses, practical exercises, industry-specific case studies, and a community forum where your team can keep developing after the formal programme ends.
That's genuinely our goal. Dependency is bad for clients. We transfer knowledge aggressively — documentation, recorded sessions, live walkthroughs, and ongoing access to learning resources — so your team becomes self-sufficient.
Every engagement ends with a formal handover checklist signed off by both teams. If your team isn't confident, the handover isn't complete.
Hard-won lessons from building production AI — embedded into every training programme we deliver.
Rapid prototyping and data validation before full model development prevents the most expensive mistakes in AI — building the right solution to the wrong problem, or discovering fundamental data issues late in the process.
Models degrade silently. Teaching teams to build monitoring pipelines from day one — tracking prediction distributions, feature drift, latency, and business metrics — prevents the silent failures that erode AI value over time.
The simplest model that meets the business requirement is often the best model. We train teams to resist over-engineering — starting with baselines, adding complexity only when proven necessary, and documenting every decision with evidence.
Treating models and datasets with the same rigour as code — versioning, reproducibility, experiment tracking, and rollback capability. Teams that skip this cannot debug, improve, or audit their AI systems reliably.
Knowing when AI should decide autonomously and when a human must review is a critical design skill. We train teams to build systems with appropriate human oversight — especially for high-stakes decisions in healthcare, finance, and legal contexts.
AI systems that teams and stakeholders can understand and interrogate are trusted, adopted, and improved over time. We embed explainability tools and techniques — SHAP, LIME, attention visualisation — into every model development workflow.
Four ways to access Cogniv AI training — each optimised for a different team structure, pace, and learning style.
Fully immersive, in-person sessions at your office or a dedicated training venue. Highest engagement, richest team dynamics, and the ability to work directly with your actual systems and data.
Instructor-led sessions over video — interactive, structured, with real-time Q&A, breakout rooms, and live coding exercises. All the rigour of in-person training with zero travel overhead.
Access the full Cogniv AI curriculum on-demand through the learning portal. Structured modules, exercises, and assessments that fit around your team's schedule — with progress tracking and completion certificates.
Individual coaching sessions with a Cogniv AI engineer for technical team members who need personalised mentorship — code reviews, architecture feedback, career guidance, and accountability for self-directed learners.
Not sure which program or support tier is right for you? Book a free 20-minute consultation and we'll help you figure it out.
Book a Free Consult →It depends on the track. The AI Leadership Bootcamp and AI for Product Builders tracks require no coding experience — they're designed for non-technical professionals. The Applied ML Engineering track requires solid Python proficiency and basic statistics. Custom domain workshops are scoped during the needs analysis to match your team's actual baseline.
Yes. We have trainers who can deliver in Hindi and several regional languages for Indian clients. For on-site and live virtual programs, just let us know your preference during scoping. The self-paced portal is currently English-only, with Hindi content in development.
Cogniv AI support is AI-specialist support — our engineers understand machine learning, model behaviour, data pipelines, and AI system architecture. We don't just close tickets; we diagnose why a model is underperforming, identify data drift, suggest retraining strategies, and help your team understand what changed. This is deeply technical, domain-specific support that a general IT helpdesk cannot provide.
We support third-party AI systems too, provided we can complete a technical onboarding review first. We'll review your system architecture, documentation, and codebase — typically a 1-week process — before committing to an SLA. If the system is well-documented, this is straightforward. Enterprise support contracts include this onboarding as standard.
Yes. All participants who complete a Cogniv AI training program receive a digital certificate of completion. For the Applied ML Engineering track, certificates are issued upon completing the capstone project with a passing review score. Certificates include QR code verification for LinkedIn and portfolio use.
Absolutely — and this is the most effective combination. Many clients start with a training programme for their team and simultaneously take on a Pro Support plan for their production systems. Clients who bundle training and support receive a 10% discount across both services for the first 6 months. Ask us about combined bundles during your consultation.
Tell us about your team, your tools, and your goals. We'll design a training and support plan that fits in 48 hours.