A practical, non‑technical subject for finance and consulting professionals making sense of AI at work. Thirty‑five courses across seven tracks, from the principles of AI and the EU AI Act through to ChatGPT, Microsoft Copilot, prompt engineering, agentic AI and Retrieval Augmented Generation. Beginner to Advanced.
Clients, regulators and partners now expect AI fluency on every engagement. This subject takes a complete beginner from the principles of AI and the EU AI Act through to everyday work with ChatGPT, Microsoft 365 Copilot and Copilot Studio, ending with prompt engineering, agentic AI and RAG. No coding background required to start.
See the learning outcomes →Written for analysts, associates and managers, not data scientists. Concepts are explained in plain language, with finance and consulting examples in every lesson.
A dedicated track on responsible AI use and the regulation that's now reshaping how it's deployed. The risk view boards and clients are starting to ask for.
ChatGPT, Microsoft 365 Copilot, Copilot Studio and the prompt‑engineering moves that make them productive. Skills used the same week they're learned.
Stretch beyond the basics with regression, classification and unsupervised learning, then onto LLMs, agentic AI and Retrieval Augmented Generation.
Every outcome is mapped to a specific lesson and assessed through scenario‑based exercises. Learners walk away with practical AI skills they can apply on the next client engagement, board pack or internal workflow.
Build the vocabulary and mental model to contribute meaningfully to AI conversations with clients, partners and the board, with no technical background required.
Principles of AIRecognise where AI is high‑risk, what the Act actually requires, and the six principles for using AI responsibly inside a regulated business.
AI & SocietyUnderstand how regression, classification and unsupervised learning are used to forecast numbers, classify outcomes and surface hidden patterns in business data.
AI Models & Use CasesKnow how Natural Language Processing and Large Language Models work, what they can and can't do, and how to interpret and adjust their output.
AI Models & Use CasesMaster ChatGPT and Copilot inside Word, Excel, Outlook, Teams and PowerPoint. Faster drafting, sharper analysis and safer use across the everyday workflow.
Generative AIFoundational and advanced prompting techniques that produce reliable output, plus a practical toolkit of patterns to reuse across the team.
Generative AIBuild a working HR copilot in Microsoft Copilot Studio, scope an agentic AI rollout responsibly, and design a Retrieval Augmented Generation pipeline end to end.
Copilot Studio, Agents & RAGAI Fundamentals is built as seven tracks. Start with the principles of AI and a non‑technical view of the EU AI Act and ethics, move through AI models and use cases, then go deep on Generative AI tooling (ChatGPT, Claude, Microsoft Copilot, prompt engineering, agentic AI and vibe coding) and Retrieval Augmented Generation, and finish with the everyday habits of working with AI: checking its output, collaborating with it, agentic work, cost and governance. A final track connects AI to systems thinking, process mapping, agents in business systems and AI strategy. Pick one track or run all seven end to end.
Start here. What AI actually is, where it shows up in business, and the most common applications a finance or consulting professional will see in client work.
A non‑technical introduction to AI. What it is, where it's used, the ethical and privacy questions it raises, and what the future may look like for jobs and society. No prior knowledge required.
Text and image analysis, speech recognition and behavioural and sentiment analysis. The most common business applications, the algorithms behind them and the kind of results to expect, all without writing code.
The risk view. The EU AI Act and the six ethical principles every team should follow when AI is involved in real decisions.
The EU AI Act is now the global benchmark for responsible AI. Learn how AI systems are classified by risk, what the Act requires for compliance, and how it affects businesses inside and outside the EU.
How AI shows up at work and why ethical use matters. Six core principles for using AI responsibly, plus how to spot risks, ask the right questions and protect the people the system affects.
The model layer. Predicting numbers, classifying outcomes, surfacing patterns, and understanding how natural language and large language models actually work.
Use AI to predict the numeric values behind business decisions. Learn the regression techniques used to forecast continuous outcomes, and how to evaluate the models that produce them.
Not every business question is a number. Learn how classification techniques predict outcomes with a limited set of possible answers, and how to evaluate them.
Hidden patterns in data often hold the most value. Learn how unsupervised learning techniques surface clusters and associations that aren't obvious from the surface numbers.
Natural Language Processing has long been a hard problem for computers, and AI is making it tractable. Learn what NLP is, where it's used, and how it works at a principled level.
The models behind chatbots and modern generative AI tools. How LLMs work, how to interpret and adjust their output, and where the technology is heading next.
The applied track. ChatGPT, Claude, Microsoft 365 Copilot, Copilot Studio, prompt engineering, agentic AI and inline AI coding. The tools and techniques every team is now expected to use.
How generative AI was built, what it can do, and where it's already adding value at work. A grounded look at the applications, the issues and the opportunities for finance and consulting teams.
The most effective way to interact with generative AI. Foundational and advanced prompting techniques, the limits of the underlying models, and a practical prompt toolkit to reuse on real tasks.
A step beyond the basics. Look under the hood at how prompts and language models interact, with techniques for generating and optimising the output you actually want.
The full ChatGPT toolkit. Interface, model selection and the advanced features that turn it from a productivity boost into a genuine working tool for complex tasks.
Copilot in Chat, Teams, Word, Outlook, PowerPoint and Excel. Safer prompts, sharper output, and how to use it responsibly across the everyday Microsoft 365 workflow.
Generative AI is reshaping the data analytics workflow. Learn how to integrate ChatGPT and Copilot into analysis, from cleaning data through to surfacing the insights leadership actually wants.
Build AI‑powered copilots without writing code. The core concepts behind copilot design, then a working HR copilot built from scratch using topics, actions and knowledge sources.
AI agents complete complex tasks on their own and shift how teams operate. Explore how agents work, see real applications, and learn how to adopt them responsibly.
Generative AI lets non‑developers ship working tools. Learn the inline, “vibe coding” style of building simple applications with AI to streamline real workflows.
A short orientation to ChatGPT: the interface, the model choices and response modes, and the core features professionals use day to day for drafting, summarizing and refining work. The first course in the ChatGPT collection.
Get productive in Claude quickly: the interface and conversation controls, model switching, Projects, artifacts, Skills and extended thinking, plus the failure modes to watch for.
Work through long documents with Claude without losing accuracy. A scope, task and format framework for document prompts, synthesis across several documents, and when Claude is the wrong tool for the job.
Move from one-off prompts to reusable set-ups: generating and refining artifacts, Projects with standing instructions and reference files, connecting a Project to a live source, and Skills for recurring work.
Using Claude to carry out file and task work across a whole project rather than a single conversation. Configure a session, extend it with files, skills, connectors and scheduled tasks, apply it to practical workflows and use it responsibly.
The technique that grounds AI in real, current data. How RAG reduces hallucinations and extends LLMs into private knowledge bases.
RAG retrieves real‑time, external information so AI systems answer with accuracy and current context. Learn how it compares to fine‑tuning, then build a mental model of the full retrieval, augmentation and generation pipeline.
How people work alongside AI day to day: judging its output, sharing and directing work, agentic working, cost awareness and responsible governance.
The fundamentals of working with any AI tool: framing a clear request, giving it the context and material it needs, reading its output critically and iterating, with trust, accountability and safe use built in.
Fluent writing is no longer evidence that content is correct. Build the judgment to decide whether an AI output can be trusted: verification habits, common failure patterns and automation bias.
Hand AI a complete piece of work and manage it from brief to finished result. Divide the work, review what comes back and keep human judgment where it belongs.
Take individual ownership of AI at work. Audit your recurring work, redesign a workflow around AI and build the habits and measures that make the change stick.
How agentic working differs from prompting: the parallel loops run by an agent and its human supervisor, and how an agent’s memory and tools set the limits of what it can be trusted to do.
What you are paying for when you use AI. How tokens are counted, what drives the cost of a request, where hidden costs build up and how to keep usage predictable.
The AI governance lifecycle: an AI register, risk classification, policy design, human oversight, monitoring and audit evidence, including how the EU AI Act is implemented in practice.
Where AI meets the wider organization: thinking in systems, mapping processes before automating them, connecting agents to business systems safely, and setting an AI strategy.
See an organization as a system rather than a chain of causes and effects: stocks, flows and feedback loops, why delays and unintended consequences happen, and how to apply systems thinking to a real situation at work.
Map a business process before automating any part of it. Build process maps with swim lanes, branches and handoffs, spot bottlenecks and single points of failure, and judge which decisions AI should and should not be trusted with.
What happens when an AI agent is given access to your systems: the look, decide, act and check loop, how APIs become an agent’s tools, read versus action access, and where to place human approval.
Turn scattered AI activity into a strategy. Evaluate use cases against value, feasibility and risk, set governance that matches your risk appetite, and build the culture that makes adoption stick.
AI Fundamentals sits inside Kubicle's wider library, alongside subjects on Excel, Power BI, Tableau, SQL, Data Literacy, financial modelling and project management. The most common starting point for finance and consulting teams getting AI‑ready.
Try for Free →Kubicle is engineered around a single goal: practical skills that get used. Every design choice, from lesson length to assessment style, is made to keep finance and consulting professionals engaged and to translate watch time into measurable outcomes at their desk.
Most lessons run 5–10 minutes. Designed to fit between meetings, not block out a Tuesday afternoon. The result: 80% completion vs. a 7% industry benchmark.
Every lesson lands in a finance or consulting context, from prompt patterns for client work to building a copilot for an internal HR query.
CPD, CPE and NASBA accreditation means credits count toward continuing professional development. Certificates are shareable on LinkedIn the moment they're earned.
Every course slots into a wider learning path. Pair AI Fundamentals with Excel, Power BI, Data Literacy or financial modelling as the team's needs grow.
Engagement and skill‑gain dashboards from day one. Leaders see exactly where capability is building and where it isn't, by team and by role.
Modules are refreshed continuously to reflect new tools, regulation and the rise of generative AI. You never pay for material that's gone stale.
The numbers, the accreditations and the customer outcomes are all on the table, so L&D, Early Careers and Practice Leads can build the business case fast.
Every course awards CPE / CPD credits via NASBA‑recognised accreditation, so time spent here counts on a CV and on the team's compliance log.
These aren't aspirational numbers. They are the measured outcomes Kubicle clients report after a typical rollout, with manager‑level dashboards from day one so practice and L&D leaders can see exactly where capability is building.
More than 60% of Kubicle learners report saving between 30 minutes and 2 hours every week thanks to sharper data and AI skills. Time redirected to higher-value work, and a measurable productivity dividend at the team level.
45% of Kubicle learners apply newly‑acquired skills daily, the difference between training that's watched and training that's worked.
75%+ of learners report measurable gains in both data analysis and the communication skills needed to make insights land with stakeholders.
Kubicle was easy to set up and our learners were quickly engaged. It's effectively closed our skill gap, especially in tools like Excel and data processing, and the real-time progress tracking and certifications are why we'll keep using it.
Validated Reviewer
TotalEnergies
Still have a question? Send an enquiry and one of our learning advisors will walk you through it within a business day.
Try for Free →Finance and consulting professionals at every level, from analysts and associates through to managers, partners and L&D leads. The thirty‑five courses are pitched non‑technically. Beginners can start at Track 01, while learners already comfortable with ChatGPT typically jump in at prompt engineering, agentic AI or RAG.
No. The Principles, Society and Generative AI tracks are entirely non‑technical. The Models and Use Cases track explains regression, classification and unsupervised learning at a principles level, with no coding required. The most advanced course, Inline Coding With AI (vibe coding), is itself designed for non‑developers using AI to build simple tools.
Roughly 36 hours of content across 35 courses, worth 35.3 CPE/CPD credits. Lessons are bite‑sized, so most learners complete the full subject in four to eight weeks of casual study, fit around real work.
Yes, both. Master ChatGPT covers the full ChatGPT toolkit, model selection and advanced features. Using Microsoft 365 Copilot covers Copilot in Chat, Teams, Word, Outlook, PowerPoint and Excel. Introduction to Copilot Studio walks you through building a working HR copilot from scratch, no coding required.
Yes. The AI and Society track has dedicated courses on the EU AI Act and on AI Ethics in the Workplace. Both are pitched for non‑legal, non‑technical audiences, covering risk classification, compliance requirements, and the six ethical principles every team should follow when AI is involved in real decisions.
Yes. Kubicle credentials are independently accredited by CPD, CPE and NASBA. Every course awards CPE/CPD credits that learners can apply toward continuing professional development. Certificates are shareable on LinkedIn the moment they're issued.
Yes. Kubicle offers off‑the‑shelf integrations with leading LMS providers and the engineering team will build a custom integration for any other system you run. SSO is supported across the board, and a Reporting API exposes engagement and completion data to your dashboards.
AI Fundamentals is a single subject inside the wider Kubicle library, which also covers Excel, Power BI, Tableau, SQL, Visualization Fundamentals, Data Literacy, Data Security, financial modelling and project management. Most teams pair AI Fundamentals with Excel or Data Literacy.
Kubicle is ISO 27001 certified, GDPR‑compliant, and undergoes regular third‑party penetration testing. Granular roles, SSO and audit logging are built in.
Of course. Send an enquiry and a learning advisor will scope the rollout, recommend the right starting point for your team, and put together a pilot proposal with a tailored quote.
Send a short enquiry and a learning advisor will come back within one business day with a tailored recommendation: a curriculum mapped to your team's roles, a sample pathway through AI Fundamentals (and any related subjects), and a quote you can take to budget. Built for teams of 5 to 100, deployable in days.