Artificial Intelligence and Supercomputing

Typology: Curiosity and interest

Are you wondering how to solve your data analytics problems quickly?

Do you have a dataset large enough to be unable to analyze it on your workstation?

In this course we will analyze a large dataset using modern Machine Learning techniques and show how to scale an algorithm, or parallelize it at key points (e.g. data pre-processing, cross validation) to simultaneously exploit the available computing resources ( from laptop to supercomputer).

Prerequisites

•     Basic knowledge of Python.
•     Familiarity with Machine Learning algorithms
•     Ability to execute code on Linux Machine
•     Basic knowledge of Machine Learning and Neural Networks

Outgoing skills

•   Knowledge of examples of machine learning and data management algorithms
•   Knowledge of HPC benefits for ML and AI
•   Knowledge related to training and hyperparameters
•   Knowledge on implementation of AI on HPC
•   Theoretical and practical knowledge of distributed training

Teachers

• Bhaskar Agarwal (Cineca’s Data Scientist)
• Laura Morselli (HPC Specialist of Associazione Big Data)
• Eric Pascolo (Cineca’s HPC Specialist)