DATA3 Academy
Upskilling teams for the AI-powered future
DATA³ Academy is the training and upskilling arm of DATA³, designed to help organisations build confidence and capability in data + AI.
We go beyond theory, combining practical, hands-on learning with real-world business impact. From foundational skills to advanced AI applications, our programmes are built around your people, your tools, and your challenges.
What makes the DATA³ Academy different?
Practical, not abstract – training grounded in live business problems, not generic examples
Tailored to you – content aligned with your sector, goals, and current data maturity
Delivered by doers – our trainers are practising consultants who implement data + AI solutions daily
Building lasting capability – we don’t just train, we help embed a data + AI culture across teams
Clarity on how to leverage data + AI
Who is the DATA3 Academy For?
Leaders seeking to understand the possibilities of AI and data
Teams needing new technical and analytical skills
Organisations looking to future-proof their workforce in a rapidly changing digital landscape
Objectives
- 1. Provide a concise overview of Data, AI + Analytics: current trends, use-cases, and key terminology
- 2. Introduce data types, the data lifecycle, and analytics maturity models
- 3. Explain AI/ML fundamentals, including common techniques, challenges (bias, data quality, ethics)
- 4. Guide leaders on assessing current data maturity and planning an AI-enablement roadmap
Outcomes
- 1. Strategic insight into how data and AI can create value and competitive advantage
- 2. A shared understanding of opportunities and risks for the organisation
- 3. Identification of 2–3 pilot projects and next steps for building capability
Objectives
- 1. Deepen understanding of data architecture, warehousing/lakes, data quality, and governance
- 2. Teach descriptive, diagnostic, predictive, and prescriptive analytics, including ML algorithms and model evaluation
- 3. Cover AI ethics, legal considerations, deployment (MLOps), and change management
- 4. Provide hands-on activities with sample datasets and tool demonstrations (Python/R, scikit-learn, TensorFlow/PyTorch)
Outcomes
- 1. Practical skills to design and execute analytics and AI projects from start to finish
- 2. Experience with key tools and techniques for data analysis and machine learning
- 3. A tailored action plan and governance framework to scale AI across the organisation
Introducing your lead trainer + transformation strategist
Dr. Kion Ahadi
Kion consults with Data Cubed’s clients on data strategy, AI adoption, and digital transformation, helping executive teams move from curiosity to capability through practical, industry-specific innovation.
As Lead Trainer on the Catalyst Series, he designs and delivers high-impact learning experiences that demystify AI and data for busy professionals. His sessions are known for blending strategic clarity with technical depth, translating complexity into actionable roadmaps that deliver measurable business value.
With over 20 years of senior leadership and board-level experience across law, housing, tech, and finance, Kion has a track record of leading large-scale transformation. He currently serves as CEO of the global legaltech platform LegaMart, is a Non-Executive Director at Data Cubed, and sits on the Board at Gateway Housing. Previously, he spearheaded a £7m digital transformation at the National Lottery Heritage Fund and delivered £9m in new digital revenue at The Law Society.
A published researcher and frequent keynote speaker, Kion has authored influential reports on AI ethics, lawtech adoption, and neurotechnology, and teaches executives worldwide through Emeritus, delivering university-backed programmes in digital transformation, analytics, and AI for leaders at organisations such as HSBC, Old Mutual, and global law firms.
He holds a PhD in Sociology, alongside certifications in Cybersecurity, PRINCE2, Data Science for Executives (LSE), and the Data Leaders Masterclass, combining academic depth with hands-on technical expertise in cloud (Azure/AWS), machine learning, governance, and MLOps.
Kion’s work is shaped by a belief in responsible innovation, making emerging technology work for people, not the other way around.