Data Scientist / ML Engineer

Overview

This practical training course is designed for data scientists and ML engineers building high-risk AI models. It focuses on meeting the strict data governance, accuracy, and robustness requirements of the EU AI Act so that models are both high-performing and regulation-ready.

What You Will Learn

• Meet Article 10 data governance requirements (quality, bias, and representativeness)
• Achieve Article 15 accuracy and robustness standards through rigorous testing
• Produce professional model cards and validation reports for compliance
• Implement compliant model development workflows from data to deployment

Who Should Take This Course

This course is ideal for Data Scientists, Machine Learning Engineers, AI Model Developers, and technical professionals responsible for designing, training, and validating high-risk AI systems.

Course Format

AI Assurance E-Learning Platform - Self-paced online, detailed.

Key Benefits

• Practical skills to develop models that satisfy Articles 10 and 15
• Ability to create strong model documentation and validation evidence
• Clear understanding of data quality and robustness expectations
• Confidence in building regulation-compliant AI models

Body of Knowledge - Mapped to Standards and Regulations

• Article 10 Data Requirements (data quality, bias detection, representativeness, EU AI Act Article 10)
• Article 15 Accuracy & Robustness (testing and validation requirements, EU AI Act Article 15)
• Model Cards & Documentation (required content for Annex IV sec.4, EU AI Act Annex IV)

Key Takeaways

• Understanding of the Data Scientist / ML Engineer role and responsibilities
• Core knowledge and practical skills for compliant model development
• Clarity on risk and control responsibilities
• Awareness of key duties and performance indicators for the role

Certificate

Participants will receive a certificate of completion upon finishing the course.