AIDA Short Course: “Nvidia DLI – Accelerating Data Engineering Pipelines”, 13th January 2023

 

 

Nvidia DLI and University Debrecen organize an online AIDA short course on “Accelerating Data Engineering Pipelines” offered through the International Artificial Intelligence Doctoral Academy (AIDA). 

The purpose of this course is to overview the foundations and the current state of the art in GPU-accelerated data science in python.

This short course will cover the following topics:

  • Data on the Hardware Level (60 mins),
  • ETL with NVTabular (120), Data Visualization (120 mins),
  • Final Project: Data Detective (60 mins)

The targeted applications will be in GPU-accelerated ETL data process.

 

LECTURER: 

– Dr. Laszlo Kovacs, Assistant Professor

Nvidia Deep Learning Institute Certified Instructor and Ambassador, email: kovacs.laszlo@inf.unideb.hu

 

HOST INSTITUTION/ORGANIZER: Nvidia Deep Learning Institute, Faculty of Informatics, University of Debrecen, Hungary

 

REGISTRATION: Free of charge for university students and staff

 

WHEN: January 13, 2022 from 09:00 to 17:00 CET

 

WHERE: Online

 

HOW TO REGISTER and ENROLL: 

Both AIDA and non-AIDA students are encouraged to participate in this short course.

 

If you are an AIDA Student* already, please:

Step (a) register in the course by following the Course Link: Nvidia Deep Learning Institute | University of Debrecen (unideb.hu) AND

Step (b) enroll in the same course in the AIDA system using the enrollment button in the AIDA course page Nvidia DLI – Accelerating Data Engineering Pipelines – AIDA – AI Doctoral Academy (i-aida.org), so that this course enter your AIDA Course Attendance Certificate.

 

If you are not an AIDA Student do only step (a).

 

*AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the AIDA Members listed in this page: https://www.i-aida.org/about/members/)

 

Dr. Laszlo Kovacs, Assistant Professor

Nvidia Deep Learning Institute Certified Instructor and Ambassador

Email kovacs.laszlo@inf.unideb.hu\

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