Part B of Smart Attica EDIH’s Training Modules for SMEs begins

GRNET, in the context of Smart Attica EDIH (European Digital Innovation Hub), announces the continuation of its successful training program with five new specialized modules. These sessions, conducted in Greek, are designed to further strengthen the digital capabilities of Small and Medium-sized Enterprises (SMEs) by providing advanced practical knowledge in Artificial Intelligence (AI), Machine Learning (ML), and High-Performance Computing (HPC).

These new training modules are ideal for software developers, data scientists, managers, and professionals seeking to expand their skills in applying related technologies and tools. Participants will gain hands-on experience that they can apply to their organization’s digital transformation efforts.

How to Register:

Interested individuals are encouraged to visit the dedicated Smart Attica EDIH page for more information and to register for the modules that align with their interests.

 

Modules Overview:

  1. Ensemble Learning Techniques
  • Date: June 2nd, 2025, at 12:00 EET
  • Description: An in-depth seminar on advanced ensemble learning techniques, focusing on Random Forests and XGBoost. This seminar will cover the theoretical foundations, practical implementations, and computer code in these powerful machine-learning methods. We will also explore hyperparameter tuning strategies to optimize model performance.
  • More: Module 7 Details & Registration

 

  1. Unsupervised Learning
  • Date: June 16th, 2025, at 12:00 EET
  • Description: This seminar will cover key methods such as K-Means, Hierarchical Clustering, Principal Component Analysis (PCA), and t-distributed Stochastic Neighbor Embedding (t-SNE). These techniques are essential for uncovering hidden patterns and structures in data without predefined labels, making them invaluable for various applications in businesses.
  • More: Module 8 Details & Registration

 

  1. Applying Machine Learning to Solve Real-world Challenges
  • Date: June 30th, 2025, at 12:00 EET
  • Description: In this hybrid (on-site and online) seminar, each participant will select a topic of interest and analyze a dataset using AI/ML techniques, train machine learning models, or utilize LLMs powered by Retrieval-Augmented Generation (RAG). 
  • More: Module 9 Details & Registration

 

  1. Multiprocessing in Python
  • Date: July 14th, 2025, at 12:00 EET
  • Description: This session is designed to equip professionals with the skills to optimize computational tasks, particularly in machine learning applications, using Python’s multiprocessing capabilities.
  • More: Module 10 Details & Registration

 

  1. CUDA in Python
  • Date: July 28th, 2025, at 12:00 EET
  • Description: An insightful seminar on leveraging GPU acceleration for linear algebra computations in Python. This session will introduce you to CUDA with CuPy, powerful tools that enable significant performance improvements in computational tasks by utilizing NVIDIA GPUs.
  • More: Module 11 Details & Registration
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