AI Fundamentals for Data Professionals

Artificial Intelligence (AI) is rapidly changing the way organizations work with data. As a data professional, you can play a key role in this! AI automates processes, recognizes complex patterns, and generates groundbreaking insights. But AI can only be successful if it is built on a solid foundation of data management and governance. Without good data, you will encounter challenges such as poor quality, lack of transparency, and ethical risks.

Are you ready to take your AI skills to the next level?
In this inspiring two-day AI training course, led by Erik Fransen and Pieter den Hamer (guest lecturer at Connected Data Academy), you will discover how to use data management and governance effectively to make AI solutions not only technically powerful, but also ethically responsible and reliable. In these interactive sessions, you will combine current theory with practical workshops, allowing you to learn directly how to successfully implement AI within your organization.

Why is this training essential for you?

• Learn the essential techniques and applications of AI in a practical way.
• Understand how you can 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 methodologies to seamlessly integrate AI into existing processes.

This training is more than just knowledge transfer; it is the opportunity to strengthen your role as a data professional and help your organization move forward in the AI era!

Are you ready to take your data and AI skills to the next level? Sign up today and discover how you can make a difference in your organization!

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 are evolving.
  • Relevance: Essential for data professionals who want to understand which AI methods are suitable for specific business problems.
• The crucial role of data management within AI
  • How data quality, metadata, lineage, and governance influence AI projects.
  • The importance of data labeling, annotation, and feature engineering.
  • Relevance: AI is only as good as the data it is trained on. This helps you set up AI projects properly from the ground up.
    Hands-on sessions with AI tools
• Demos and practical examples with AI platforms such as MindsDB, Azure ML, KNIME, and RapidMiner.
  • Experimenting with data preparation and model development yourself.
  • Relevance: Theory is useful, but applying AI tools yourself makes it truly practical.
• Generative AI and its 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: Organizations are increasingly looking for ways to implement Generative AI responsibly. Here you will learn how.
• AI governance and compliance: risks and regulations
  • 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 managing these risks.
• Action plan for AI in your organization
  • How do you organize collaboration between AI and data teams?
  • What governance and management provisions are still missing?
  • Relevance: You will leave the training not only with knowledge, but also with a concrete plan to strengthen AI within your organization.

Who is this training for?

This training is intended for data professionals with a 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 link AI to governance and compliance.
• BI specialists who want to use AI for advanced data analysis.
• Data scientists who want to optimize their models with better data management.
• AI strategists and managers who want to deploy AI responsibly within their organization.

Why participate?

After this training, you will have the knowledge and skills to apply AI responsibly and effectively. You will 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 provided by experienced experts Erik Fransen and Pieter den Hamer (guest lecturer at Connected Data Academy), who share both theoretical knowledge and practical experience. Through interactive sessions, practical cases, and hands-on exercises, you will be able to translate AI concepts directly into your own work environment.

Are you ready to take your AI knowledge to the next level? Sign up and develop a future-proof vision on AI and data management!

No specific technical knowledge is required—the training is both in-depth and practical.

The two-day program:

Day 1: Classical AI and Data Management

Introduction & Objectives

• Introduction and setting learning objectives

Session 1: Introduction to AI

• Classic AI techniques: heuristics, search algorithms, expert systems
• Machine learning models: regression, decision trees
• 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 Fundamentals

• Data governance, metadata, lineage, and quality
• Data labeling, annotation, and cataloging

Lunch break

Demo: Preparing Data for Data Science

• Hands-on workshop: cleaning, structuring, and annotating data

Session 3: Data Governance and AI – Risks and Regulations

• AI legislation: AI Act, GDPR, bias, fairness, and security

Break

Online Quiz: AI and Data Governance

• Testing acquired knowledge

Group discussion: AI and Data Governance in practice

• Working out a practical case study

Day 2: Generative AI and AI Governance

Introduction to LLM, SLM, LAM, and AI Agents

• Generative AI: OpenAI, Google Gemini, Meta’s LLaMA
• Contextualizing foundation models (RAG, fine-tuning)

Demo and discussion: Prompt Engineering & RAG

• How do you optimize 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 legislation
• IP rights and ethical considerations

Trends and Developments

• Composite AI, synthetic data, and fake data
• AI in data management: augmented data integration, data fabrics

Break

Concluding workshop: Action plan for AI in your organization

• Organizing collaboration between AI and data teams
• Strengthening process and governance

Closing and certificate presentation

The training is provided by experienced experts Erik Fransen (head trainer at Connected Data Academy) and Pieter den Hamer (guest lecturer at Connected Data Academy), who share both theoretical knowledge and years of practical experience. Through interactive sessions, practical cases, and hands-on exercises, you will be able to directly translate AI concepts to your own work environment.

After completing this training, you will receive a professional development certificate. This certificate demonstrates that you have not only actively participated, but also invested in deepening your professional skills at the intersection of data, AI, and governance. It is a valuable recognition of your growth as a data professional in a rapidly changing field.