Ship production-ready code with AI. Code safely, quickly, and with proof you can show. The Vibe Coding 1 Day Accelerator is an intensive 8-hour online workshop from the Academy of Digital Industries designed to plug AI coding assistants into your existing development workflows. Across one full day, you will master structured prompting, AI-assisted testing and code review, agentic workflows, and Model Context Protocol (MCP) fundamentals.Guided by our mentors, AI engineers Dan Porder and Uvin Withana, and supported by Community Managers, you will graduate with portfolio-ready artefacts including a technical plan and prototype, AI-generated test suites and debugging notes, and a risk and accountability pack.Who is this course for?Build on your existing engineering expertise and add practical AI-assisted workflows. Learn how to plug AI safely into your day-to-day coding, testing, documentation and review standards.Who should join this course?Software engineers and full-stack web or app developers shipping to productionData scientists and ML / AI engineers who maintain real services and pipelinesTech leads, senior ICs and staff engineers standardising team workflowsDevOps, SRE and platform engineers adding AI into build, test and release processesQA and automation engineers adopting AI for test generation and debuggingContractors and freelancers who need portfolio artefacts that prove capability to clientsYou already code in your day job; this is not a learn-to-code course, and no prior AI or ML experience is required.We know that formal language certifications such as B2 can be time-consuming and expensive, and many of our learners do not hold them. We do expect you to be comfortable communicating in English and to be working in a professional environment where English is used regularly.Learning outcomes and objectivesBy the end of the workshop, you will be able to:Write precise, context-rich prompts that produce reliable, production-quality codeApply AI-assisted workflows for testing, code review, debugging, refactoring and documentationOrchestrate agentic development flows and apply Model Context Protocol (MCP) fundamentals in practiceUse AI tools to analyse, modernise and document legacy codebases efficientlyIdentify, assess and mitigate risks related to intellectual property, data security and compliance in AI-assisted developmentYou will also develop the mindset to move from coder to architect, using AI strategically across the software lifecycle rather than treating it as a one-off tool.Background – why this matters for working developersThe landscape for developers is changing fast. AI coding tools are no longer side projects – they sit inside the editor, shaping how code gets written, reviewed and deployed.Mainstream adoptionAbout three in four developers now use or plan to use AI tools in their workflows. → If you are not learning to direct these tools, you risk being the person who just checks AI output. (Stack Overflow Developer Survey 2024: https://survey.stackoverflow.co/2024)Proven efficiency gainsIn controlled experiments, developers using GitHub Copilot completed tasks around 55% faster than those without it. → AI can already match or beat you on speed. Your edge has to come from architecture, judgement and governance. (GitHub blog, 2023: https://github.blog/news-insights/product-news/research-how-github-copilot-helps-developers)Productivity reshapedMcKinsey and others show that generative AI shifts time away from repetitive coding and towards higher-value work – design, integration, problem-solving. → Teams that get this right ship more, with the same headcount. (McKinsey, 2023: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier)Shifting rolesField studies on generative AI show workers finish tasks faster and report higher satisfaction – but the biggest gains go to those who learn how to use AI well. → The gap is opening up between paste prompts into a box and run disciplined AI workflows. (NBER Working Paper No. 31161: https://www.nber.org/papers/w31161)Employer investmentAnalysts forecast AI software and GenAI spend to reach hundreds of billions of dollars within a few years, including tools for software engineering and developer productivity. → Your company is going to spend money on AI either way. The question is whether you are the person who knows how to make that investment pay off in code quality, not just speed. (IDC, 2023: https://www.idc.com/getdoc.jsp?containerId=US51106123)Governance gapMost tutorials and courses teach how to use the tools, not how to build accountable, testable and auditable workflows around them. That leaves a gap between this looks clever and I would sign my name to this in a production incident review.The Vibe Coding 1 Day Accelerator is designed to sit exactly in that gap: it assumes you already code, and focuses on disciplined AI-assisted workflows, agentic patterns and governance that your tech leads can defend.Reasons to believeBuilt for working professionalsWeekend, live-online delivery with feedback loops means you can apply what you learn directly to your current codebase without stepping out of your role.Mentors who actually ship with AIMentorship from Dan Porder (and Uvin Withana) brings experience from places like IKEA AI Lab and Valae, anchoring the syllabus in real, production AI systems – not just toy examples.Portfolio and workflow focusYou do not just watch demos. You leave with a technical plan, prototype, AI-generated tests and debugging work, and a risk and accountability pack you can use in performance reviews and interviews.Tool-agnostic, governance-first Instead of locking you into one editor or subscription, the course teaches patterns you can apply across Copilot, Cursor, Claude Code and future tools – with testing and governance baked in from the start.Stronger ROI than yet another tutorialFree intros (Microsoft Learn, YouTube, and so on) and subscription libraries (O’Reilly, DeepLearning.AI on Coursera, and so on) are great for awareness, but they rarely give you accountable workflows or artefacts your organisation will recognise. This accelerator is designed around job-ready outputs and cohort-based practice, not passive content.School HighlightsPractical focus: every part of the day is anchored in real coding tasks and portfolio artefacts, not just theoryGovernance-first design: accountability, testing and risk mitigation are embedded throughout the workshopMentor expertise: learn directly from practitioners with global industry experience, including IKEA AI Lab and leading AI studiosOnline delivery: live weekend sessions with recordings available so you can revisit materialCommunity and alumni: ongoing access to a professional network of peers and alumniB2B credibility: options for custom cohorts, tailored dashboards and ROI check-ins for organisations

Increase efficiency, improve productivity and gain ROI.The Generative AI Accelerator is a five week online course from the Academy of Digital Industries designed to plug AI skills into your expertise. Across evening workshops, participants master advanced prompting, multi‑prompt pipelines, vision‑language tools, image generation, data strategy, governance, and ROI frameworks.Guided by one of our Mentors, Dan Porder or Uvin Withana, and supported by Community Managers, learners graduate with two portfolio ready final projects chosen from Prompt Library, Multi Stage Automator, Image Generation Brand Book, and an AI Strategy Proposal, and an Academy digital Completion Certificate.Who is this course for?Build on your expertise and add practical AI skills. Learn to plug AI into your day-to-day workflows and standards.Who should join this course?Professionals across marketing, design, communications, product and operationsEntrepreneurs and small business ownersEnablement teams and cross functional cohorts standardising AI across the businessNo prior AI background requiredWe understand that formal certifications like B2 can be long and expensive, and many of our learners may not have them. However, we do expect learners to have conversational English and to be working in a professional environment where English is used regularly.Learning outcomes and objectivesBy the end of the course, you will be able to:Identify and prioritise high value AI opportunities in your role or team using a simple scoring modelDesign and run prompt systems that turn a brief into a repeatable workflow with guardrailsTeach students how to iterate on prompts through versionsCreate a brand image generation guide that produces consistent, on-brand imagery across channelsProduce an AI strategy proposal that frames the business case, risks, governance and an adoption plan for leadershipApply evaluation checks, bias awareness and data protection basics to any workflow, and complete a light risk checklistCommunicate ROI with simple KPIs such as hours saved, quality lift, cost avoided, improved revenue and profitBackground: Why it matters nowAI has moved from novelty to necessity. Organisations need practical, safe, and measurable ways to deploy AI:Governance and risk (policy, standards, bias, data security, explainability) sit alongside innovation as board level concerns'Do more with less' budgets force in-house capability building and tighter ROI proofProductivity and speed are top priorities across teams - but ad-hoc prompting rarely scalesIt's important to understand the wider market data, too:Adoption (UK): 18% of UK businesses reported using at least one AI or generative AI tool in late March 2025; Among large firms (250+ employees) adoption was 31%. 77% said they were not planning to adopt AI in the next three months [S1]Enterprise value at stake: Generative AI could add roughly $2.6 to $4.4 trillion in annual value across functions globally, with major impact in sales, marketing, customer operations and software engineering [S5]Skills gap (UK): 16% of firms cited the level of AI expertise and skills as a barrier to AI adoption in 2023, according to ONS's Management and Expectations Survey [S2]Wage premium for AI skills: Jobs requiring AI skills carry up to a 25% wage premium in some markets (2024), rising to an average 56% in 2025 [S14]Training gap: Only around 1/3 of employees receive proper employer provided AI training; Microsoft's 2024 Work Trend Index found 39% of users had received training [S15]