Course Outline

Advanced Neural Networks

  • Deep learning architectures
  • Convolutional and recurrent neural networks
  • Generative models and unsupervised learning

Machine Learning at Scale

  • Big data analytics
  • Distributed computing for ML
  • Advanced optimization techniques

Reinforcement Learning and Decision Making

  • Markov decision processes
  • Policy gradient methods
  • Multi-agent systems and game theory

Natural Language Processing and Understanding

  • Advanced NLP techniques
  • Sentiment analysis and text classification
  • Language models and transformers

Computer Vision and Perception

  • Image recognition and object detection
  • Video analysis and action recognition
  • 3D reconstruction and augmented reality

AI Ethics and Society

  • Bias and fairness in AI systems
  • AI governance and policy
  • Future societal impacts of AI

Lab Project

  • Implementing advanced ML models
  • Analyzing large datasets
  • Collaborating on a group research project

Summary and Next Steps

Requirements

  • A solid understanding of basic AI and ML concepts
  • Proficiency in Python and familiarity with data science toolkits
  • Completion of an introductory course in AI or equivalent experience

Audience

  • Data scientists
  • Engineers
  • AI practitioners
 21 Hours

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 4800 € + VAT*

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