Gain a solid foundation in ML core concepts.

Explore supervised and unsupervised learning, master data management and quality control techniques, and understand the critical role of MLOps in production environments.

ML Basics & Principles

Learn from Industry Leaders about:

  • Supervised vs. Unsupervised Learning: Explore the two paradigms of ML and how they are used to solve different types of problems.
  • Data Management and Quality: Learn best practices for handling ML datasets while ensuring data integrity and quality
  • Real-World Applications: Discover ML applications across industries from recommender systems to fraud detection
  • Challenges and Considerations: Gain insights into key challenges like data bias, explainability, and ethical considerations.

Track Speakers London 2026

Track Speakers San Diego 2026

San Diego's program will go live soon! Until then, please take a look at

New York's 2024 Program!

Track Speakers Munich 2026

Track Speakers New York 2025

Track Speakers Amsterdam 2026

Track Speakers Berlin 2025

Track Program London 2026

Track Highlights San Diego 2026

Track Program Munich 2026

Track Program New York 2025

Track Program Berlin 2025

Track Program Amasterdam 2026

Track Sessions London 2026

Track Sessions London 2026

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Track Sessions Amsterdam 2026

Track Sessions Amsterdam 2026

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Track Sessions San Diego 2026

Track Sessions San Diego 2026

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Track Sessions MLcon Munich 2026

Track Sessions MLcon Munich 2026

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Track Sessions MLCon New York

Track Sessions MLCon New York

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Track Sessions MLcon Berlin 2025

Track Sessions MLcon Berlin 2025

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Behind the Tracks

Generative AI & Agents
Unlock the future of AI with LLM advancements.

MLOps & LLMOps
Bridge the gap between model creation and real-world application.

ML & Deep Learning
From Feature Engineering to Explainable AI.

AI Strategy & Governance
Transform business processes with AI-driven strategies.

AI Developer Tools
Build next-generation machine learning applications.

ML Basics & Principles
Gain a solid foundation in core ML concepts.