Build enterprise AI capability,
from awareness to architecture.

Our AI training spans the full stack — from AI awareness for business teams to hands-on Generative AI, large language models, RAG, prompt engineering, AI agents, and production deployment for engineers. Programmes are role-based and mapped to how your teams actually work.

Every programme is live and instructor-led by practitioners, delivered on our Orbit platform with hands-on labs. It is not pre-recorded — participants work through real problems with a trainer, not a video.

Live instructor-led courses include Generative AI with Deep Learning, Agentic AI with LangChain and LangGraph, MLOps and LLM Deployment, Machine Learning, and Machine Learning with Python. Enterprise tracks can be customised to your stack.

Yes. Most of our enterprise delivery is private batches, customised to your tools, schedule, and skill levels. Individuals can also join scheduled open batches through the training calendar.

Yes — participants receive a Greater Insights certificate on completion, backed by hands-on project work rather than attendance alone.

Structured, live training that gets a company's teams using AI well — from prompt-writing and generative-AI tools for business users to LLMs and MLOps for engineers. Done right it's hands-on and tied to real work, not a lecture on what AI might do someday.

Teach the tool and the guardrails together. People learn to get real value from GenAI and to spot its failure modes — hallucination, data leakage, weak prompts — so they use it with judgement. Safe use is a skill, and it's learned by doing under guidance.

Yes — arguably more than the engineers. Marketing, ops, finance and HR now use AI daily, often without knowing where it goes wrong. A short, practical programme turns ad-hoc dabbling into confident, governed use across the business.

It splits by role. Business teams need prompting, AI-tool fluency and judgement; analysts and engineers need LLMs, RAG, MLOps and responsible-AI practice; leaders need enough to govern it and measure impact. The mistake is training only the technical few.

ChatGPT's a practical tool your team should understand, but it's not AI training itself. We show you how to use large language models responsibly in your organisation—what they're actually good for, where they'll disappoint you, and the risks you need to manage.

We run hands-on sessions where your team works with Claude, ChatGPT and similar models—not just theory. You'll learn prompt engineering, spotting hallucinations, and integrating these tools into real workflows. That's what sticks.

Machine learning is a subset of AI. Our programme covers both—where ML means training models on data, AI is broader: chatbots, automation, decision systems. You need context for each. We run it all together so your team sees how they connect.

We're live and in-person with your team—you bring real problems, we work through them together. No pre-recorded videos. Your people get answers to their actual questions, not a generic curriculum.

ChatGPT is a conversational model—useful for drafting and brainstorming. But your organisation needs broader AI literacy: understanding when to use different tools, spotting hallucinations, embedding AI into workflows safely. We train your team on practical application, not just one platform.

We don't specialise in single-tool training. Instead, we teach your team how large language models like Claude actually work—their strengths, limitations, risks—so you can deploy them confidently across your organisation, whatever tool you choose.

We're hands-on and live. You work through real scenarios with your own data, not pre-built modules. Your team leaves with practical capability and context specific to your business—not just certificates.

We cover how ML and generative AI actually differ, where each fits your strategy, building datasets, spotting bias, managing risk. You'll understand what's realistic for your organisation and make smarter investment decisions—not just learn theory.

ChatGPT is one generative AI interface, but enterprise teams need broader capability. You'll want training covering prompt engineering, responsible AI use, and integrating various tools into your actual workflows—not just learning a single platform.

Claude is useful, but focusing solely on one tool limits your team. Better to learn foundational AI concepts, evaluation methods, and how to choose the right model for your specific problems—then apply that thinking to whichever tool fits.

We run hands-on, live sessions with your actual team and real problems—not pre-recorded content. You'll work through genuine enterprise scenarios, get immediate feedback, and build capability your organisation can actually use.

Proper AI/ML training covers fundamentals, model evaluation, responsible deployment, and how to integrate these into your existing systems. You'll need both technical depth and business context—that's where live, tailored programmes make the difference.

ChatGPT's a large language model—good for drafting and brainstorming. But your team needs to understand its limits: hallucinations, data privacy concerns, and when to use purpose-built tools instead. We run hands-on sessions covering generative AI fundamentals so you know what each tool actually does.

Yes. Claude's another large language model with different strengths—often better at reasoning and following instructions precisely. Rather than tool-specific courses, we train your team on how to evaluate and safely deploy these models in your workflows, whichever you choose.

We're live, hands-on, and tailored to your enterprise context—not generic online modules. You work with real scenarios your team faces, ask questions directly, and leave with practical capability. That's different from self-paced platform learning.

AI and ML are distinct. AI's the broader field; ML's a subset using data to train models. Our courses cover when to use each, how they work practically, and—crucially—what your team needs to manage them responsibly in production environments.

ChatGPT is one generative AI model—useful for text tasks, but your organisation needs broader capability. We train your team on how different AI tools solve real problems: when to use ChatGPT, when Claude works better, how to integrate them safely into your workflows without breaking compliance or data security.

We don't focus on single tools. Instead, we teach your team how to work with modern large language models—Claude, ChatGPT, open-source alternatives—so you understand each one's strengths and limitations. That way, you choose what actually fits your business needs, not hype.

Great Learning offers self-paced, theory-heavy content. We run live, hands-on sessions where your team builds real AI applications—not just learning concepts, but actually shipping things. You leave with working knowledge your organisation can use Monday morning.

We split it: AI foundations (how models actually work, limitations, risks), then practical ML—building, evaluating, deploying models safely. Most importantly, we show your team how to think critically about AI in your specific context, not treat it as magic.

ChatGPT's a consumer tool—useful for experimenting, but enterprises need more. Our training covers how to evaluate AI tools for your actual workflows, security requirements, and integration needs. You'll learn what ChatGPT does well and where you need purpose-built solutions.

We don't specialise in single-tool courses. Instead, we teach your team to understand AI fundamentals, evaluate different models (including Claude), and implement them safely in your organisation. That way you're not locked into one vendor—you can adapt as tools evolve.

Most online platforms are self-paced and pre-recorded. We're live, hands-on, and built for your team's specific context. You'll work on real problems with our instructors, not watch videos alone. Better for embedding change that actually sticks.

Machine learning is a subset of AI. If you're evaluating tools like ChatGPT or building data pipelines, you need AI literacy. If you're developing models in-house, you need ML depth. We can tailor programmes to your team's role and your organisation's actual goals.

ChatGPT's a useful tool for exploring generative AI, but your team needs deeper understanding of how it works, its limits, and how to integrate it safely into your organisation. That's where hands-on training comes in—moving beyond prompts to actual capability.

Claude's another large language model worth understanding, but a proper course teaches you how to evaluate different models, understand their trade-offs, and build real solutions. You'll learn when to use what—not just learn one tool.

Most online courses are self-paced lectures. If your team needs hands-on, instructor-led training where you actually build and troubleshoot AI solutions together, that's a different proposition—one that sticks and transfers to your real work.

Machine learning is a subset of AI—it's about training models on data. AI training is broader: it covers ML, but also generative AI, prompt engineering, deployment, and governance. Your team likely needs both perspectives to work effectively.

ChatGPT-specific training focuses on practical prompting, integration into your workflows, and understanding its limitations. Most courses treat it as theory—we show your team how to actually use it in your business, avoiding common pitfalls and maximising what it can genuinely do for you.

Look for hands-on practice with Claude's actual capabilities, not just marketing claims. You need to understand its strengths in reasoning and analysis, how it compares to alternatives, and how to integrate it into your systems. Theory alone won't help your team use it effectively.

We specialise in live, hands-on training with real enterprise problems—not pre-recorded content. Your team works with actual tools and data, learns from practitioners, and leaves with skills they can apply immediately. That's different from most online courses.

Start with AI fundamentals if you're new to the field—it covers broader concepts and practical tools like ChatGPT. Machine learning is more specialised and math-heavy; take it after if you need to build custom models. Most organisations benefit from AI skills first.

ChatGPT is one LLM among many. For your team, what matters is knowing when to use it, how to integrate it safely into your workflows, and what it can't do. We run hands-on sessions covering practical deployment across different tools—not just ChatGPT worship.

Yes. We cover Claude alongside other major models, focusing on where it excels—longer context windows, reasoning tasks—and how to build real applications with it. Training's practical, not theoretical; your team learns by doing.

We don't do vendor certifications. Instead, we run accredited programmes that teach your team to evaluate and deploy generative AI tools—including Claude—with genuine capability you can apply immediately to your organisation's work.

Our programmes cover prompt engineering, fine-tuning, integration patterns, and governance for teams building with LLMs. Hands-on, not slides. You'll work on real problems your organisation faces, with practitioners who know what actually ships in production.

Yes. We run live, practical programmes on Claude's capabilities—prompt engineering, API integration, fine-tuning where relevant. Your team works through real scenarios, not theory. You'll leave knowing how to deploy it properly in your stack.

We don't offer formal vendor certifications, but we run rigorous, hands-on Claude training where your team builds real projects and proves competence. That's more valuable than a certificate—your people can actually ship.

We design custom programmes for your developers: prompt design, RAG architectures, integration patterns, safety considerations. Live, interactive, grounded in your actual problems—not generic courses. We've worked with teams across finance, tech, and professional services.

ChatGPT is one option, but your organisation needs to understand its strengths and limits. We run hands-on training covering ChatGPT alongside Claude, Gemini and others—so your team knows which tool solves which problem, how to prompt effectively, and what security considerations matter to you.

Yes. We deliver live, practical Claude training tailored to your organisation's workflows. Rather than generic overviews, we focus on real tasks your team faces—whether that's content work, analysis or coding—so you leave confident and capable.

Formal certifications from Anthropic are limited, but we offer accredited training that documents your team's Claude competency. What matters more: your people actually knowing how to use Claude well. Our programmes prove that through practical application, not just a badge.

Ours covers Claude's strengths—reasoning, long context windows, nuanced outputs—and how to integrate it into your workflows. We pair theory with hands-on labs, so your team leaves with proven skills and templates ready to deploy tomorrow.

ChatGPT is one large language model among several. For your team, the real question isn't which tool, but how to use any of them safely and effectively in your organisation. We train you on prompt engineering, risk assessment, and integration patterns that work across different AI platforms—so you're not locked into one.

Yes. We run hands-on Claude training alongside ChatGPT, Gemini, and other models. Rather than tool-specific theory, we focus on practical use: how to structure prompts, evaluate outputs, manage security, and embed AI into your actual workflows.

We don't issue vendor-specific certs, but we do verify competency through live projects and assessments. Your team leaves with demonstrated skills—not a badge. That's usually what hiring managers and internal stakeholders actually want.

We run hands-on developer programmes covering prompt design, API integration, safety testing, and deployment. You work with real code and real models—not slides. Suits teams building AI features, not just using off-the-shelf tools.