AI Fundamentals for Data Professionals
This two-day AI training for data professionals offers an in-depth introduction to both classic and modern AI techniques, with a strong focus on the link between AI, data management and governance. The training enables professionals to make the most of AI within their existing data governance frameworks.
Artificial Intelligence (AI) is rapidly changing the way organisations work with data. As a data professional, you can play a key role in this. AI automates processes, recognises complex patterns and generates breakthrough insights. But AI can only succeed when it is built on a solid foundation of data management and governance. Without good data, you run into challenges such as poor quality, lack of transparency and ethical risks.
Ready to take your AI skills to the next level?
In this inspiring two-day AI training, delivered by Erik Fransen and Pieter den Hamer (guest lecturer at Connected Data Academy), you discover how to use data management and governance effectively to make AI solutions not only technically powerful, but also ethically responsible and trustworthy. In these interactive sessions you combine up-to-date theory with hands-on workshops, so you learn directly how to implement AI successfully within your organisation.
Why is this training essential for you?
Learn the essential AI techniques and applications in a practical way.
Understand how to strengthen AI projects with effective data management and governance.
Discover how to prevent poor data quality, lack of transparency and ethical risks from undermining your AI projects.
Get concrete tools and methods to integrate AI seamlessly with existing processes.
This training is more than knowledge transfer. It is the opportunity to strengthen your role as a data professional and help your organisation move forward in the AI era.
Ready to take your data and AI skills to the next level? Sign up today and discover how you can make the difference in your organisation.
What can you expect?
A solid foundation in classic AI techniques
Insight into heuristics, search algorithms, expert systems and machine learning.
Understand how these techniques are applied in practice and how they evolve.
Relevance: essential for data professionals who want to understand which AI methods fit specific business problems.
The crucial role of data management within AI
How data quality, metadata, lineage and governance affect AI projects.
The importance of data labelling, annotation and feature engineering.
Relevance: AI is only as good as the data it is trained on. This helps you set up AI projects right from the start.
Hands-on sessions with AI tools
Demos and real-world examples with AI platforms such as MindsDB, Azure ML, KNIME and RapidMiner.
Experiment yourself with data preparation and model development.
Relevance: theory is useful, but applying AI tools yourself makes them truly usable.
Generative AI and the impact on data management
Insight into foundation models, RAG (Retrieval-Augmented Generation) and fine-tuning.
Data preparation for Generative AI, including vector databases and information retrieval.
Relevance: organisations increasingly look for ways to implement Generative AI responsibly. Here you learn how.
AI governance and compliance: risks and regulation
How data governance frameworks such as DAMA-DMBOK contribute to AI management.
AI Act, GDPR, ethics, bias and security risks such as data poisoning.
Relevance: AI brings new risks. Knowledge of governance and compliance is crucial to manage them.
Action plan for AI in your organisation
How do you organise collaboration between AI and data teams?
Which governance and management provisions are still missing?
Relevance: you leave the training not just with knowledge, but with a concrete plan to strengthen AI in your organisation.
Why take part?
After this training you have the knowledge and skills to apply AI responsibly and effectively. You learn how to set up and manage data science and AI projects, gain insight into the latest AI trends and discover how AI and data governance come together.
The training is delivered by experienced experts Erik Fransen and Pieter den Hamer (guest lecturer at Connected Data Academy), who share both theoretical knowledge and hands-on experience. Through interactive sessions, real-world cases and hands-on exercises, you translate AI concepts directly into your own work.
Ready to take your AI knowledge to the next level? Sign up and develop a future-proof vision on AI and data management.
The two-day programme
Day 1: Classic AI and Data Management
Introduction and objectives
Meet each other and set learning goals
Session 1: Introduction to AI
Classic AI techniques: heuristics, search algorithms, expert systems
Machine learning models: regression, decision trees
The AI process and the role of data professionals
Data quality and drift monitoring
Demos: knowledge-driven and data-driven AI
Applications of AI in real-world cases
Break
Session 2: Data Science and Data Management, the foundation
Data governance, metadata, lineage and quality
Data labelling, annotation and cataloguing
Lunch break
Demo: preparing data for Data Science
Hands-on workshop: cleaning, structuring and annotating data
Session 3: Data Governance and AI, risks and regulation
AI regulation: AI Act, GDPR, bias, fairness and security
Break
Online quiz: AI and Data Governance
Check what you have learned
Group discussion: AI and Data Governance in practice
Work through a real-world case
Day 2: Generative AI and AI Governance
Introduction to LLMs, SLMs, LAMs and AI Agents
Generative AI: OpenAI, Google Gemini, Meta's LLaMA
Contextualising foundation models (RAG, fine-tuning)
Demo and discussion: Prompt Engineering and RAG
How do you optimise AI models?
Coffee break
Data preparation for Generative AI
Information retrieval, vector databases and knowledge graphs
Lunch break
AI Governance for Generative AI
Privacy, compliance and regulation
IP rights and ethical considerations
Trends and developments
Composite AI, synthetic data and fake data
AI in data management: augmented data integration, data fabrics
Agentic AI and context engineering / semantic layers
Break
Closing workshop: action plan for AI in your organisation
Organise collaboration between AI and Data teams
Strengthen process and governance
Wrap-up and certificate ceremony
After completing this training, you receive a professional development certificate. This certificate shows that you not only took part actively, but also invested in deepening your professional skills at the intersection of data, AI and governance. A valuable recognition of your growth as a data professional in a fast-changing field.
Audience
This training is for data professionals with basic knowledge of data management and data engineering:
Data engineers who want to understand how AI models integrate with data pipelines.
Data stewards who want to connect AI to governance and compliance.
BI specialists who want to use AI for advanced data analysis.
Data scientists who want to optimise their models with better data management.
AI strategists and managers who want to deploy AI responsibly within their organisation.
Prior knowledge
No specific technical prior knowledge is required. The training is both in-depth and practically accessible.