2024-07-22 AI Training Series - Introductory AI Workshop by Intel (hdta6s24)

Online CourseAI Training Series - Introductory AI Workshop by Intel
Numberhdta6s24
Available places87
Date22.07.2024 – 22.07.2024
PriceEUR 0.00
LocationONLINE
Room
Registration deadline15.07.2024 23:59
E-maileducation@lrz.de


This course has been shifted from the old date 17.06.2024 to the new date 22.07.2024.

This course is part of the "LRZ AI Training Series", a series of courses aiming at the needs and expectations of data analytics, big data & AI users at LRZ. While focusing on these particular users and their use cases, this session as well as all other courses offered as part of the AI Training Series are, of course, open to all interested parties.

This course for academic participants from Germany will be organised as an online event.

Contents

Accelerated Machine Learning with Intel (Morning Sessions)

  • Introduction
  • Welcome & presentation of the day's agenda and speakers.
  • Hardware acceleration for AI and Intel® oneAPI AI Analytics Toolkit
    In this session, we will first introduce the hardware features that power and accelerate AI on Intel hardware.
    We will then take a first look at the software stack that leverages them, namely the Intel® oneAPI AI Analytics Toolkit.
  • Introduction to the Intel® Tiber™ AI Solutions Portfolio

    • Intel® Tiber™ Developer Cloud (ITDC)
      The Intel® Tiber™ Developer Cloud (ITDC) offers AI cloud services on managed, high-performance and cost efficient infrastructure, enables users to build & deploy AI models, applications and solutions at scale with early access to latest Intel  hardware including Intel CPUs  and  Gaudi™ AI accelerators.
    • Intel ® Tiber ™ AI Studio (formerly cnvrg.io)
      The Intel ® Tiber ™ AI Studio is a comprehensive machine learning platform that simplifies and accelerates the end-to-end AI workflow. It offers seamless integration with various hardware configurations, including Intel CPUs and Gaudi accelerators, providing robust tools for model development, training, and deployment.
  • Introduction to the Intel Distribution for Python, Data Parallel Extensions for Python, and Accelerating Classical Machine Learning on Intel Hardware
    In this session we will show you how to boost your classical machine learning models on Intel hardware. We will explore the use of Intel Extension for Scikit-learn, and libraries like daal4py to accelerate XGBoost and LightGBM models. Learn about leveraging the Intel Distribution for Python and optimizations for numpy, scipy, and parallel extensions (dpnp, dpctl, numba-dpex) for running Python on Intel CPUs and GPUs.

Accelerated Deep Learning with Intel (Afternoon Sessions)

  • Generative AI Powered by Intel
    In this session, we present to you the most recent advancements in Generative AI, covering Large Language Models and Diffusion Models. We will explore how Intel plays a crucial role in powering this technology, from training and fine-tuning to inference across a spectrum of Intel hardware platforms.
  • Introduction to Distributed Deep Learning across Intel Hardware
    In this session, we will talk about Distributed Deep Learning and how it can be effectively implemented on Intel's cutting-edge hardware platforms. We will cover topics like why Distributed training is required, explore various techniques of neural network parallelism, will cover various tools like such as Intel oneCCL, Distributed Data Parallel (DDP), Horovod, Fully Sharded Data Parallel (FSDP), and DeepSpeed which are essential for scaling of AI model.
  • Hands-On Session with Intel Tiber Developer Cloud - running IPEX on Intel Hardware

The presentations will be accompanied by demos to demonstrate the performance improvements.
The course is organised by LRZ in cooperation with Intel.

Prerequisites

  • Basic knowledge of Python
  • AI Training Series: Orientation Session (or comparable previous knowledge)
  • Good understanding of Deep Learning and Classical Machine Learning (courses such as Introduction to Deep Learning (I2DL) (IN2346) are provided by TUM - material also available for non-TUM students)

Language

English

Lecturers

Sneha Chattopadhay, Akash Dhamasia, Stefana Raileanu, Severine Habert (all Intel)

Prices and Eligibility

The course is open and free of charge for academic participants from Germany.

Registration

Please register with your official e-mail address to prove your affiliation.

Withdrawal Policy

See Withdrawal

Legal Notices

For registration for LRZ courses and workshops we use the service edoobox from Etzensperger Informatik AG (www.edoobox.com). Etzensperger Informatik AG acts as processor and we have concluded a Data Processing Agreement with them.

See Legal Notices


No.DateTimeTeacherLocationRoomDescription
122.07.202410:00 – 16:00Ajay NavilarekalONLINE
Lecture