+31 (0) 73 203 22 71 info@connecteddatagroup.com

Data Science Fundamentals

Training on the growing need for Machine Learning, Data Mining and AI applications alongside traditional BI tools. Explores the differences between BI, Data Warehousing, Big Data and Data Science.

1 day
Certificate on completion
data-science

There is a growing demand to deliver, alongside familiar business intelligence (BI) applications such as reports, dashboards and OLAP, also Machine Learning, Data Mining and Artificial Intelligence (in short: Data Science) applications for and with users. In this course we explore the differences between Business Intelligence, Data Warehousing, Big Data and Data Science, and show what Data Science is, why it is relevant for BI and Data Warehouse professionals, and how you can apply it in practice.

What can you expect?

After this course you can name the different concepts and steps in Data Science, take part in the conversation and advise on tools and implementation.

What will you learn?

After this training, you have insight into:

  • The fundamental role of Data Science in the current data landscape

  • The differences and similarities with Business Intelligence

  • The variants of Data Science: Data Mining, Machine Learning and Artificial Intelligence

  • Concrete Data Science examples from practice

  • A deep-dive into the different algorithms for Data Science

  • An overview of well-known and lesser-known tools

  • Several demos of Data Science tools

Training setup

The training combines theory with concrete real-world examples and assignments. You learn from experienced trainers with hands-on experience.

Why take part?

You learn how to apply Data Science to your own work and which tools and methods are available. That way you lay a solid foundation for successful projects and contribute directly to data-driven decision-making.

Sign up today and build a solid foundation in Data Science.

During the course you gain insight into fundamental and current developments in the Data Science field, and which questions you can solve with Data Science. The focus is on creating insight into how the different themes connect.

Topics covered:

  • Overview of Data Science

    • What is data science and what are the differences and similarities with BI and data warehousing?

    • Which questions can we solve with data science?

  • The relationship between big data and data science

    • Data Mining

    • Predictive and descriptive models: how do you choose and how do you apply them?

    • Supervised and unsupervised learning

    • Overview of data mining forms (classification, clustering, association)

  • Machine Learning

    • Overview of machine learning algorithms

    • Building models, making the right choices

    • Neural networks, decision trees, genetic algorithms: what can you do with them and how do they work?

    • Deep learning: on the way to artificial intelligence

  • Artificial Intelligence

    • What is artificial intelligence?

    • The differences with data mining and machine learning

    • AI in daily practice: what do we already notice?

  • Data Science in practice

    • Case: Clinical Decision Support

    • Case: Smart Environmental Zone

  • Data Science roles

    • From BI Competence Center to Data Science Competence Center: from data-driven to data-centric

    • From BI consultant to Data Science consultant: developing a new skill set, what does it look like?

  • The Data Science process

    • CRISP-DM: methodology for Data Science

    • Step-by-step plan for implementing Data Science

    • Risks, pitfalls and measures

  • Tool demos

    • Demo RapidMiner Data Science Platform

    • Demo MS Azure Machine Learning

    • Demo TIBCO Spotfire Predictive Analytics

  • Tool overview and advice

    • RapidMiner, SAS, IBM, KNIME, Microsoft, TIBCO, MapR, R, Python

  • Tips and advice for a successful Data Science project

    • Setting up business cases and use cases for Data Science

    • Plan of approach for Data Science projects

    • Success and failure factors

    • Five tips to take home

After completing this training, you receive a Professional Development certificate as proof of the knowledge and skills you have gained.

Audience

Professionals with a BI and Data Warehousing background who want to understand Data Science.

Prior knowledge

No specific technical knowledge required. Affinity with data, BI or IT projects is an advantage.

data-science
27 mei 2026
Nieuwegein Available
Wednesday 27 May 2026 09:00 – 17:00
Register until 20 May 2026
€ 720,00