Put Responsible and Sustainable AI into Practice
AI is taking up an ever more important role in software development, with core software functionalities being replaced by machine learning models. However, the use of such adaptive techniques is not without drawbacks. They may use a lot of energy, introduce bias, and have discriminatory effects. Building ethical and sustainable AI is therefore no longer optional -- it's essential for business success and social impact.
This training focuses on building AI solutions that are not only powerful but also ethical, responsible, and sustainable.
Praktische info:
Inschrijven?
- Voorwaarden: Experience with coding and basic knowledge of Python, scikit-learn, and Pandas.
- Prijs: SMEs, and midcaps: Free ; Large companies and participants without a company: €3031
Bring your computer
georganiseerd door:
Leertraject
Participants will learn to discover and handle drawbacks and gaps in a classification pipeline through the operationalisation of responsible and sustainable AI practice. Specifically, participants will learn practical techniques for and gain a solid understand of:
- How to improve the performance of ML systems for minorities
- How to assess fairness of ML techniques
- how to lower the need for large amounts of data.
- Strengths and weaknesses of different evaluation metrics.
- Sources of bias that may introduce discrimination.
- How to improve the robustness of algorithmic outcomes.
- Awareness of potential secondary effects that are not modelled in data.
Key Features
Hands-on training through problem-based learning: Start solving classification problem, reflect in group, and learn from each other's.
Coding in pairs: Partner in pairs based on personal preferences for coding.
Actionable takeaways: Walk away with practical techniques and actionable skills to immediately integrate responsible, ethical, and sustainable AI strategies into projects.
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