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Generative AI Accelerator
A Course Delivered By Industry Expert Dan Porder

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 our Mentor, Dan Porder 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.
- Learn how to cut costs, speed up delivery and improve revenue.- in just 5 weeks.
- Next Start Date: 27th Oct 2025
- Course Type: Live online
- Location: Anywhere
- Time: 19:00-21:00 BST (Mon & Thurs)
- Course Fee: £600 (early bird discount available)
- Mentor: Dan Porder, AI engineer, educator and business owner
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 operations
Entrepreneurs and small business owners
Enablement teams and cross functional cohorts standardising AI across the business
No prior AI background required.
Learning Outcomes And Objectives
By 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 model.
- Design and run prompt systems that turn a brief into a repeatable workflow with guardrails.
- Teach students how to iterate on prompts through versions.
- Create a brand image generation guide that produces consistent, on brand imagery across channels.
- Produce an AI strategy proposal that frames the business case, risks, governance and an adoption plan for leadership.
- Apply evaluation checks, bias awareness and data protection basics to any workflow, and complete a light risk checklist.
- Communicate ROI with simple KPIs such as hours saved, quality lift, cost avoided improved revenue and profit.
Background: Why It Matters Now?
AI 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 proof
- Productivity and speed are top priorities across teams – but ad‑hoc prompting rarely scales.
It’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 or more 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 percent wage premium in some markets (2024), rising to an average 56 percent in 2025. [S14]
- Training gap: Only around one third of employees receive employer provided AI training; Microsoft’s 2024 Work Trend Index found 39 percent of users had received training. [S15].
Meet Your Mentor

Dan Porder is an AI engineer, educator and content engineer. He is the cofounder of Valae and previously served as Senior AI Content Engineer in the IKEA AI Lab. Valae is an AI engineering studio that builds production generative AI systems for consumer brands, from customer service automation and knowledge agents to brand safe image generation, with governance and evaluation built in. Selected brands include IKEA, Bugaboo and Moco Museum.
Module Content
Nine modules and final projects delivered over a five week course.
1. Introduction to AI
- Introduction and preview to course
- Definition and history of artificial intelligence
- What is data?
- What is machine learning?
- What is GenAI and why did it rise so quickly?
- GenAI as a general-purpose technology
- Limitations of GenAI
- Integrating GenAI into daily tasks
- Exercises and discussion
2. AI for Productivity
- Overview of major AI tools (ChatGPT, Claude, Gemini, DeepSeek, Microsoft Copilot, DALL-E, MidJourney, Perplexity, Whisper, Sora)
- Primary tasks that GenAI tools can be used for
- Creating
- Reading and analysing
- Thought partnering
- Researching
- Practice exercises in creating and analysing
- Checking AI answers and evaluating
- Introduction to AI bias, hallucinations, and security concerns
- Determining if AI fits your task
- What tasks AI can NOT do
- Discussion: How can AI be applied to your work?
3. Prompt Engineering with ChatGPT
- Basics of prompt engineering / prompt design
- How large language models (LLMs) work
- Randomness in output
- Context window limitations
- Prompting best practices
- Personas, tasks, formats
- Prompt patterns (e.g. question refinement, cognitive verifier, audience persona, flipped interaction, game play, meta language creation, recipe, alternative approaches, ask for input, outline expansion, menu actions, fact check list, tail generation, semantic filter)
- Practice exercises for prompt techniques
- Iterative approaches and prompting work cycle
- Exercise in building a prompt for your job
4. Advanced Prompting
- Advanced prompting techniques
- Few-shot prompting
- Chain of thought reasoning
- Meta prompting
- Prompts as a tool for repeated use (e.g. prompt templates)
- Multi-prompt pipelines and turn-based prompting
- Prompting for image analysis
- Intro to computer vision
- Intro to vision-language models (VLMs)
- OCR
- Image captioning
- Visual question answering
- Combining text and image for contextual understanding
5. Prompting for Image Generation
- Intro to AI image generation
- How diffusion models work
- Prompting best practices for image generation
- Visual imagery language
- Style modifiers
- Medium and genre definition
- Camera and lighting trigger words
- Composition and perspective
- Focal points
- Weighting
- Negative vs. positive prompting
- Defining aspect ratios
- Practice exercises for these techniques
- “Prompt battle”: Group exercise to generate accurate images
6. How to Engage with AI-driven Projects as a Non-technical Person
- How AI can be leveraged for software applications (e.g. RAG, agents, orchestration, etc.)
- How to plan around the lifecycle of an AI/ML project
- Fine-tuning vs. off-the-shelf models
- How to select the right model
- How is quantitative evaluation done? (automated & human)
- How is qualitative evaluation done?
- Leveraging subject matter experts and building diverse teams
- Cost intuition
- Data strategy
- The value of structured data
- How to ensure data is structured over time
- Considerations for metadata
- Data curation and planning: It’s more subjective than you think!
- Discussion: How would you engage with AI projects at your company?
- Introduction to final project for course
7. AI Strategy for Business
- What’s the ROI of AI projects?
- Revenue drivers
- Cost reduction potential
- KPIs of AI projects
- Prototyping/MVP approaches
- AI org setups
- Research-orientated orgs
- Applied engineering orgs
- How to gain strategic alignment across functions
- Communicating AI to stakeholders
- Practice exercise in communicating an AI project
- How to collaborate directly and indirectly with an AI team
- AI governance in a corporate setting – strategically controlling the tools, data, and implementation across your organization.
- Is AI even necessary?
- Common pitfalls due to AI hype
- Does every company need a chatbot?
- How to effectively choose an AI project
- AI as a solution to longstanding problems, rather than a novelty
- The UX of AI
- Practice exercise in AI user experience design
- Customer-focused metrics
8. Responsible AI
- Introduction to AI ethicsGo
- Discussion: What are the ethical questions around AI?
- Bias
- Inaccuracy
- Data security
- Explainability and transparency
- Who owns AI content?
- Regulations
- When AI goes wrong: Prominent examples from the news
- AI vs. humans
- Risks of job replacement
- Can AI answer opinion questions?
- Opinion in evaluation
- The question of creativity
- Final project updates – Ask questions, get guidance
9. The Future: Keeping Up with AI
- Final project presentations
- Keeping up with AI: Hype vs. usefulness
- AI and the future of the economy
- Jobs of the future
- Augment vs. reallocate vs. displace
- Unseen labour (data labelling, moderation, human feedback)
- Data as a scarce/limited resource
- The digital divide
- The potential for automation across different sectors
- AI in society and culture
- Artificial general intelligence (AGI)
Project Options
Students choose any two projects from the list below. You can mix an executional and the strategic project.
Executional projects:
- Project: Develop 5-10 advanced prompt templates for repetitive tasks in a specific job (e.g., Marketer, Graphic Designer, HR Manager, Entrepreneur, Teacher, etc.). These prompts should go beyond simple tasks and instead automate more complex parts of that job.
- Learnings Applied: Prompt engineering, prompt templates for repeated use, integrating AI into daily tasks.
- Deliverable: A structured “playbook” containing the prompt library, with clear instructions on when and how to use each prompt, including examples of inputs and ideal outputs.
- Project: Design a multi-prompt pipeline that accomplishes a complex end-to-end task. This involves chaining several prompts together, where the output of one prompt becomes the input for the next. For example, a multi-stage marketing automator could be a workflow that takes a product concept or early research, generates a tagline and pitch, creates a campaign outline, creates copy and visuals for various channels, and finally puts them together into usable assets, all automatically. Alternatively, it could be a pipeline that ingests a long-form article or video transcript and generates a series of social media posts, a newsletter summary, and key takeaways.
- Learnings Applied: Multi-prompt pipelines, iterative prompting, using AI for creating and analyzing.
- Deliverable: A detailed flowchart of the workflow, the full sequence of prompts used, and a final output example.
- Project: Create a detailed style guide for generating consistent, on-brand AI images for a real or fictional company.
- Learnings Applied: AI image generation, prompt engineering.
- Deliverable: A “Brand Imagery Prompt Book” that defines the brand’s visual identity with specific prompt formulas, style keywords, and a gallery of successfully generated images that demonstrate consistency. Also, a discussion of potential limitations.
Strategic project:
- Project: Identify a significant challenge or opportunity within your own company (or choose a case-study company) and develop a thorough proposal for an AI project to address it.
- Learnings Applied:
- AI Business Strategy: Identifying high-value opportunities, focusing on ROI of AI, defining KPIs, solving longstanding business problems, determining if AI is truly necessary.
- AI Project Planning: AI product design, selecting the right technical strategy, identifying and aligning stakeholders, collaborating with engineering and ML teams.
- Data and Governance: Developing a data strategy, addressing the need for structured data, practicing responsible AI (including security).
- Deliverable: A 5-10 page proposal document or slide deck outlining the business problem, the proposed AI solution, broad strokes technical outline, ROI analysis, key success metrics, governance/responsibility framework, and a high-level project plan or roadmap.
Why Choose This Course At The Academy
- Plug AI into your expertise, not around it. Your standards, workflows and guardrails drive the system.
- Built by practitioners, for practitioners. Every template and evaluation method mirrors real enterprise deployments. Whether you’re in our London classroom or dialing in remotely, you’ll get the same high‑touch, interactive experience and leave with artefacts you can use the very next day.
- Production over theory. You learn the same patterns Dan uses at Valae and previously piloted in IKEA’s AI Lab.
- Mentor credibility. Instructor Dan Porder translates cutting-edge AI concepts into safe, repeatable workflows.
- Guided, not self‑served. Community managers maintain momentum; recordings keep you on track.
- Lifetime network. Join ADI’s global alumni for jobs, events, and peer support.
- Market-ready, not hype-driven. We teach what teams can safely implement today, based on real adoption and budget trends.
What You'll Walk Away With
- Two portfolio ready projects chosen from Prompt Library, Multi Stage Automator, Image Generation Brand Book, and an AI Strategy Proposal.
- Safe deployment playbook including knowledge of AI in relation to corporate governance, risk checklist and evaluation plan.
- Prompt assets including a small library of reusable templates with usage notes.
- A ninety day plan to scale your workflows inside your team.
- Post‑course: 30‑day access to session recordings and resource library
- An academy digital Completion Certificate.
How You'll Learn
- 100% live online
- Schedule – 2x/week (Mon & Thurs, 19:00-21:00 BST)
- Support – Community Manager check-ins, mentor feedback, peer network
- Access – Recordings available for 30 days post-course
Entry Requirements
Open access course – no prior AI background required. Learners will need:
- A laptop with modern browser and reliable internet.
- (Optional) Access to workplace data or briefs for capstone contextualisation.
- (Optional) A low-tier paid account to ChatGPT or Claude or Gemini, but it is not essential.
- Commitment to complete applied assignments between sessions.
What Learners Say





93% of learners said our courses met its goals
94% praised the support and expertise of our mentors
93% found the environment supportive and inspiring
Global Stats
Ready To Get Started
Launch your Generative AI career with confidence. Join the next live AI Accelerator and graduate with portfolio-ready projects you can showcase and apply the very next day. Seats are limited. Secure yours now.
FAQs
Not at all. This course is beginner-friendly and built for those starting from scratch. We teach you everything you need to know and support you every step of the way.
- Two portfolio ready projects
- Safe deployment playbook
- Prompt assets
- A ninety day plan
- 30‑day access to session recordings and resource library
- An academy digital Completion Certificate.
You can bring safe, non‑sensitive data or anonymised briefs for maximum relevance. Note, using non-sensitive data is no problem, we can sign post you to open source data.. However, if you want to use proprietary or otherwise sensitive data, you will likely need a paid AI account. From there, the mentor can teach students how to ensure data protection during use, which is usually a matter of adjusting the settings of your account.
No coding required; we focus on systems, prompts, workflows and collaboration.
Hours saved, cycle‑time reduction, cost‑avoidance, and adoption scores.
A mix of leading Large Language Models (LLMs) and image tools; we teach transferable patterns, not vendor lock‑in.
Yes, you will receive a digital Certificate of Completion upon completion of your final project presentation.
To secure your spot on our course all you need to do is fill out the form on the right hand side of this page and a learning advisor will be in touch.
Absolutely. The hybrid format is built with busy people in mind. With evening classes and the option to join online or in-person, you can fit learning around your schedule.
Reach out to us directly at hello@academyofdigitalindustries.co.uk
Ready to Get Started?
Book your spot today and launch your next career move in just 5 weeks!