Data Blueprint & AI/Vibe Coding
Not a traditional coding bootcamp, and not a prompt trick. Two days that give you trusted data foundations and a method for building real products with AI — for builders who want results, not syntax drills.
Module 2 of this training is our standalone Learn Vibe Coding masterclass — if you already know your data foundations, you can take that on its own.
- Level
- Builder
- Duration
- 2 days
- Prerequisites
- None
- Delivery
- Bootcamp · Accelerator · Mastery
- Certificate
- Certificate of Completion
- Audience
- Entrepreneurs, builders, innovators
Why you need this training
Software is now built by directing AI — and the products that hold up are the ones built on data that is understood, modelled and governed. Most people learn only one half. They know their data but cannot build, or they can prompt an AI into a demo that falls apart the moment a real dataset, a real business rule or a real user arrives.
This training teaches both halves, in the order they belong. Day 1 is the Data Blueprint: decision support systems, what data and metadata are, the building blocks, modelling, processing and storage, architecture, governance and agentic AI. Day 2 is the Learn Vibe Coding masterclass in full — the eight documents, the guardrails and the build sequence, shown live on a real repository — followed by hands-on time on your own idea.
It is a method, not a course of slides: plan, build, test, deploy, improve. You leave with the documents, the constitution file and the habits that keep an AI coding agent reliable — and with the data foundations that make what it builds worth trusting.
- You can describe the product you want but cannot brief a developer — or an AI — precisely enough to get it
- You have tried AI coding tools and got something that almost worked, then broke when the data or the rules changed
- You work with data every day but have never been shown how it should be modelled, governed and made trustworthy
- You are paying for software, or waiting in a queue for it, that a small well-built internal tool could replace
Training highlights
- Build AI-powered applications
- Explore freelance opportunities
- Create corporate solutions
- Launch startup MVPs
- Module 1 · Data Blueprint — ten data-foundations topics in one day
- Module 2 · the full Learn Vibe Coding masterclass, then build time on your own idea
Who is this for
Who can take this training
For professionals who want the data foundations and to build with AI — not one without the other. Basic business or technology awareness helps; no coding is required.
Choose your pace
Flexible learning formats
All formats cover the same curriculum, learning outcomes, exercises and certification requirements. The only difference is the pace of delivery.
Most popular
Bootcamp
- Duration
- 2 days
- Schedule
- 8 hours per day
- Total time
- 16 hours
Best for
- Entrepreneurs and startup founders
- Corporate innovation teams
- Product managers
- Professionals seeking rapid results
Best for working professionals
Accelerator
- Duration
- 2 weeks
- Schedule
- 10 working days · 2 hours per day
- Total time
- 20 hours
Best for
- Working professionals
- Corporate teams
- Business analysts and product owners
- Teams needing time between sessions to practise
Best for beginners
Mastery
- Duration
- 4 weeks
- Schedule
- 20 working days · 1 hour per day
- Total time
- 20 hours
Best for
- Students and universities
- Beginners
- Career transitioners
- Long-term structured learning programmes
Participant numbers
- Malaysia — in person only, minimum 25 participants
- Outside Malaysia — online per person; in person from 100 participants, cost discussed separately
- Pakistan — in person from 100 participants, online from 10 participants, arranged through our local partner
Learning outcomes
What you will learn
- Explain how an organisation turns data into decisions, and what data, metadata, master, reference and transactional data are
- Model data from business concepts to a physical, AI-ready design, and choose the storage and processing pattern that fits the workload
- Apply the DAC Architecture framework and the four pillars of data trust — governance, security, privacy and quality — to a real data landscape
- Transform ideas into product requirements
- Generate product specifications using AI
- Design user interfaces
- Create prototypes
- Build applications using AI-assisted development tools
- Direct an AI coding agent from a written vision to a working product with guardrails
- Test and improve solutions
- Deploy working applications
- Iterate and enhance products
After this training
Start freelancing or lead data-and-AI work straight after
You leave able to offer, scope and deliver work that combines trusted data with AI-built software:
- Audit and model a client's data landscape — entities, master and reference data, metadata, and where it all lives
- Write the Vision, BRD and FSD documents for a product so an AI — or a developer — can build from them
- Build landing pages, internal tools and prototypes with an AI coding agent, inside a constitution and Git
- Set up the governance, quality and privacy basics an organisation needs before it can trust its data
- Scope and quote a small build with a work breakdown you can defend
- Know when a job needs a professional developer or data engineer — and what to hand them
Training content
Curriculum
2 modules · expand any module to see what it covers
01Module 1 · Data Blueprint
Day 1 — the data foundations every AI-era builder needs: from decision support systems to governance and agentic AI.
AI-powered product development fundamentals
Outcome: understand how AI is changing the way products are designed and delivered.
- · Traditional versus AI-assisted development
- · What is vibe coding?
- · Opportunities and limitations
- · Product thinking
- · AI-powered innovation
Decision support systems (DSS)
Outcome: understand how organisations turn data into decisions, and the anatomy of a Decision Support System.
- · What a system is — people, process and technology working together
- · OLTP vs OLAP — operational systems vs analytical systems
- · Components of a Decision Support System
- · Real-world DSS examples across banking, telecom, oil & gas and healthcare
What is data
Outcome: build data literacy from first principles — entities, attributes and how raw data becomes insight.
- · Entities, attributes and instances
- · Tables, columns and rows
- · States and types of data
- · The DIKW pyramid — Data, Information, Knowledge, Wisdom
- · Best practices and guidelines for working with data
What is metadata
Outcome: understand metadata as the layer that gives data meaning, trust and usability.
- · Business, technical and operational metadata
- · Data assets, and why metadata unlocks their value
- · Case studies — banking, telecom, oil & gas and retail
- · The cost of inaction: what happens without metadata
Building blocks of data
Outcome: understand the four building blocks every enterprise depends on, and how they work together.
- · Master data — stable, reusable core entities
- · Reference data — codes, classifications and standardisation
- · Transactional data — high-volume business events
- · Case studies — banking, telecommunications, oil & gas and healthcare
Data modelling
Outcome: navigate the full modelling landscape, from business concepts through to physical, AI-ready design.
- · Business, conceptual and information modelling (NIAM, ORM, FCO-IM, ontologies, knowledge graphs)
- · Conceptual, logical and physical data modelling, including normalisation (1NF–6NF, BCNF, DKNF)
- · Specialised techniques — dimensional, Data Vault, Anchor, Focal Point, NoSQL, temporal, event-driven
- · Governance and AI extensions — metadata modelling, access control, ML feature modelling
Data processing & storage
Outcome: understand how data is stored and processed at scale, and which pattern fits which workload.
- · Data warehouse, data lake, lakehouse, data hub and data fabric
- · Relational vs NoSQL — key-value, document, columnar and graph databases
- · Specialised datastores — Hadoop, object storage, file and table formats
DAC Architecture
Outcome: apply the founder's own DAC (Data & AI Cognitive) Architecture framework to modern data platform design.
- · Why traditional architecture fails, and the cost of architectural drift
- · Operating models — centralised, decentralised, data mesh, data hub, data fabric
- · DAC's design principles, layers and "one door in, one window out" integration
- · Traditional architecture vs DAC — what changes and why
Data governance, security, privacy & quality
Outcome: understand the four pillars of trust in enterprise data, and the roles that keep them working.
- · Data governance — ownership, stewardship, policies and decision rights
- · Security vs privacy — the CIA triad and responsible data use
- · The six dimensions of data quality
- · The real cost of getting any one pillar wrong
Agentic AI
Outcome: understand what agentic AI actually is, why many projects get scrapped, and where it creates real business value.
- · The evolution of AI, and the current reality of agentic AI adoption
- · Core agent types and how agentic AI works
- · The PVP (Productionizable Viable Product) approach
- · Real business use cases — HR onboarding, meeting automation, policy discovery
02Module 2 · Learn Vibe Coding
Day 2 — the Learn Vibe Coding masterclass in full (also offered on its own), then hands-on build time on your own idea.
Part 1 · Foundations (about 60 minutes)
- · What is Vibe Coding, and what it is not
- · What is an LLM, and what is RAG
- · Tokens, context window and why the AI forgets
- · Hallucination and how to verify what the AI tells you
- · Tools: ChatGPT, Gemini, Grok, Claude, and the coding agents (Claude Code, Cursor, Gemini CLI, Copilot)
- · Git and GitHub: your undo button
- · What is a framework, and the minimum stack you need (front end, back end, database, hosting)
- · What AI tools cost, and what is free
Part 2 · Working with AI (about 45 minutes)
- · What is Prompt Engineering, and the prompt patterns that work (role, context, constraints, examples, output format, iterate)
- · The constitution file: rules the AI must follow in every session
- · What is an Agent
- · How to make an Agent (live demo)
- · What is a Skill
- · How to make a Skill (live demo)
- · When not to use an Agent
Part 3 · The Vibe Coding Method (about 30 minutes)
- · Step 1 · Create Vision.md
- · Step 2 · Create BRD.md
- · Step 3 · Create FSD.md
- · Step 4 · Create HLD.md
- · Step 5 · Create LLD.md, including the data model
- · Step 6 · Create Project Plan WBS.md for the whole project
- · Step 7 · Create TechStack.md
- · Step 8 · Create GuardRails.md
- · Find sample sites or product designs to share with the AI
- · Give a theme image
- · Keep a decision log
Part 4 · Watch it build (about 35 minutes, live on a real repository)
- · Build the wireframe
- · Build the physical data model, and approve it before it is applied
- · Build the production product, milestone by milestone
- · Build the admin panel
- · Commit after every step, review what the AI changed, test before saying "done"
Part 5 · Guardrails and next steps (about 20 minutes)
- · Five ways vibe-coded projects fail: scope creep, invented rules, unverified claims, secrets pasted into chat, no version control
- · What comes after: testing, security, deployment, running it (covered in the 2-day programme)
- · Your Starter Kit: the eight templates, constitution template, prompt sheet, tool and cost sheet
- · The 30-day capstone challenge
Optional hands-on (30 minutes)
- · Write your own Vision.md with AI, and generate the wireframe prompt from it
The approach
Your learning journey
01
Idea
Start from a real problem worth solving.
02
Data foundations
Trusted, governed data underneath — Module 1.
03
Plan
The eight documents, Vision through GuardRails — Module 2.
04
Guardrails
The constitution the AI must never break, and Git as the undo button.
05
Build
Direct an AI coding agent milestone by milestone, inside the rules.
06
Test
Review every change and test before saying "done".
07
Deploy
Production readiness and adoption.
08
Improve
Iterate on what you shipped — the loop starts again.
Organisations that invest in AI-powered product development can:
- Accelerate innovation
- Reduce development cycles
- Improve idea validation
- Increase productivity
- Enable citizen development
- Improve business agility
- Reduce time-to-market
Take-aways
What you get out of this training
- A Certificate of Completion with a unique ID and public verification page
- Course material — a hard copy when you attend in person, a soft copy when you attend online
Investment
Course investment
Pricing is shown by region. Participants in Malaysia pay by card in RM; participants outside Malaysia and Pakistan pay by card in USD; participants in Pakistan pay through our local partner, not by card.
Rest of the world (USD)
75% OFFToday’s investment
Discount: 75% OFF · you save USD 3,000
How you payCard payment in USD
Online training price. In-person training needs a minimum of 100 participants; cost discussed separately.
Malaysia (RM)
50% OFF- Via HRD Corp
- RM 5,000minimum 25 participants
- Without HRD Corp
- RM 2,500RM 5,000minimum 25 participants
How you payCard payment in RM
In-person training price. Minimum 25 participants. There is no online option for this training in Malaysia.
Pakistan (Rs.)
55% OFFToday’s investment
Discount: 55% OFF · you save Rs. 100,000
How you payPayment through our local partner
Online training price. In-person training needs a minimum of 100 participants; cost discussed separately.
Please contact us — our local partner will contact you to arrange payment through local banks or in cash.
Contact usCan’t pay by card?
Please contact us — we will make sure our local partner contacts you, anywhere in the world, to arrange payment through local banks or in cash.
Prices are as currently published and reflect a time-limited launch offer, shown in each region’s own currency. Corporate and private-cohort engagements are quoted separately — talk to us about your team.
Who delivers this
Taught by a practitioner
Mustafa Qizilbash (opens external site)
Founder & Lead Trainer
24+ years · enterprise data & AI
More than two decades building enterprise data and AI platforms across banking, energy, telecom and government — now teaching the capability he has practised.
Certification
This training awards a certificate of completion. That is deliberately distinct from the Academy credential, which is earned through assessed applied work judged by a qualified assessor — taking part in a training is part of that pathway, and attendance alone is never sufficient. How certification works
Questions
Frequently asked
Do I need to be able to code?
No. Neither module assumes a coding background. Day 1 is about data, not programming; Day 2 teaches you to direct an AI coding agent rather than to type code yourself. If you already code, the method makes you faster and more reliable — it does not start you over.
Is Module 2 the same as the Learn Vibe Coding training?
Yes. Module 2 is the Learn Vibe Coding masterclass in full — the same six parts, from the same curriculum — followed by hands-on build time on your own idea that the half-day session does not have room for.
Can I take only Module 2?
Yes. Learn Vibe Coding is offered on its own as a half-day session for people who already know their data foundations. If you take it first and want the data half later, talk to us about dates and how that session counts towards this training.
What do I bring?
A laptop and one AI account — a free tier is enough. A GitHub account is optional but useful for the build time on Day 2. Bring a real idea, or a real dataset, if you have one: the hands-on time is yours.
Do I get a certificate?
Yes — a Certificate of Completion for this training, with a unique ID and a public verification page, issued on attending both days. It records completion of the training; it is not the Academy's earned credential.
Related resources
Related trainings
Learn Vibe Coding
Build software by directing AI — the method, the tools and a real build, in one afternoon
- Duration
- 3–4 hours
- For
- Founders, product owners, analysts, managers, curious professionals
- Format
- Half-day workshop · Live online
Bring this training to your team
Public dates are not yet published. Register your interest, or talk to us about running this as a private cohort — on-site, live online, or internationally.