Machine Learning – State of the Art
Reference : DATA-ML-STATE-01
Price : Contact us
Level & Prerequisites :
Duration : 2 days
General knowledge of data and statistics
Prior exposure to machine learning is a plus
This course offers a clear, concise, and up-to-date overview of modern machine learning, from its fundamental concepts to the most advanced approaches.
It covers classic models, deep learning methods, recent architectures, business applications, and emerging trends such as generative AI, foundational models, and self-supervised learning.
It is designed for decision-makers, data scientists, engineers, and professionals who want to understand the rapid evolution of the field and its practical applications.
Description
Data scientists, data analysts, data engineers.
IT architects and innovation managers.
Data/AI project managers.
Decision-makers seeking to understand the opportunities of machine learning.
Anyone interested in the evolution of AI.
Public
Understand the fundamental concepts of Machine Learning.
Discover the families of classic and modern models.
Explore advanced architectures: deep learning, transformers, foundation models.
Identify business use cases in different sectors.
Understand the challenges of performance, scalability, governance, and ethics.
Gain a strategic vision of current and future trends in ML.
Course objective
Introduction to Machine Learning
Major Model Families
Deep Learning: Modern Architectures
Generative AI and Advanced Models
ML Infrastructures and Tools
Business Use Cases
Governance, Ethics, and Regulation
Emerging Trends
Summary and Recommendations