Course Information

  • 1 day
  •  

    17 June

    2 September

Investment

The investment for the training is €995 per participant, excluding VAT.

Included are the training day, lunch and refreshments.  

AI for Data Science

From messy datasets to meaningful outcomes: apply AI within the CRISP DM framework to work faster, explore data more effectively, and build stronger analytical results. 

The Business Challenge

Data scientists and analysts are under pressure to deliver insights quickly while keeping accuracy and transparency high. Reading and cleaning data, exploring patterns, building predictive models, and writing good code all take time and careful attention. AI tools like Copilot and ChatGPT can help a lot, but without a clear method they can also create mistakes or shallow results. How do you use AI to speed up data science work while keeping the quality of your analysis strong?

Expert Guided Program

In this hands on program you will apply AI directly to data science tasks to:

  • Read, wrangle and prepare data: create cleaning scripts, find unusual values, and automate repetitive steps.
  • Visualize data clearly: make useful plots, explore relationships, and build AI supported visual summaries.
  • Build predictive models with machine learning: set up model pipelines, compare algorithms, tune settings, and understand model results.
  • Improve your coding skills with AI: create Python or R code quickly, fix errors faster, clean up code, and build reusable templates for repeated tasks.

Business First Approach

We focus on practical examples and real datasets based on statistical thinking and modern data workflows. You will use AI in a structured way that supports your expertise instead of replacing it, allowing you to make an immediate impact in your daily work.

Who Should Join

  • Data scientists and data analysts working with any type of data
  • Reliability and quality engineers expanding into data driven work
  • Business analysts supporting decisions with data
  • Teams responsible for modeling, reporting, and data preparation

With this training you’ll learn:

    •  Speed up data preparation with AI supported cleaning, transformation and anomaly detection, so you can move from raw data to usable datasets much faster. 
    •  Create clear and informative visualizations quickly, helping you explore patterns and communicate insights with confidence. 
    •  Build predictive models more efficiently by using AI to suggest algorithms, tune settings and explain model behavior. 
    •  Improve your coding workflow by letting AI help you write scripts, fix errors and create reusable templates, allowing you to focus your time on analysis instead of repetitive tasks. 

Teaching professionals.

Harm Derks

Harm Derks

Reliability & Data Analytics Specialist
Harm developed himself as a reliability engineer at Holland Innovative. With his background in mathematics and data analytics, he is able to understand, analyze and solve complex problems. He excels in statistical analysis, predictive modeling and process automation, allowing him to identify critical insights and implement solutions.

AI for Data Science

AI for Data Science

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Practical information.

For whom

The AI for Reliability training is designed for professionals who want to understand how Artificial Intelligence can support reliability and maintenance practices, or professionals who are regularly involved in reliability improvement, failure analysis, testing, or maintenance initiatives.

 

 

Certificate

At the end of the session, participants will receive a declaration of participation.

Location & Dates

Location

Eindhoven – High Tech Campus 29

Dates 2026

17 June

2 September

Group size 

Maximum number of participants: 12.