Training in Deep Learning

Through instructor-led demonstrations and self-paced hands-on exercises, ICHEC provides training on the latest techniques for applying deep learning techniques across a variety of application domains. Participants will explore widely-used deep learning frameworks on GPU-accelerated platforms and network with industry leaders.


AI training workshops from ICHEC


Intensive Onboarding

A 5-day training course to introduce fundamental concepts in deep learning, along with an overview of prominent and widely-used deep learning frameworks. Training will include demonstration of use-cases along with hands-on exercises using the frameworks on GPU-accelerated platforms. Training will be augmented with guest lectures and networking sessions involving industry leaders in deep learning and AI.

Course Structure

  • Programming basics for deep learning (Optional)
  • Deep learning concepts and related machine learning fundamentals
  • Every session contains hands on practical experience
  • Introduction to deep learning frameworks : Microsoft Cognitive Toolkit (CNTK) / Google Cloud AI and TensorFlow / PyTorch / Caffe2 / MATLAB
  • Guest lectures and demonstrations :

Microsoft     nvidia


MatLab   Intel    



Learning Outcomes

  • Understanding of key components in machine learning and deep learning
  • Ability to identify use-cases for machine learning and deep learning
  • Awareness of features and usability of prominent deep learning frameworks
  • Ability to use the deep learning frameworks on a cloud platform






Pre-requisites for participants

  • Approximately 1 year of programming experience with Linux and database knowledge
  • Basic algebra
  • Personal laptop computer

Date and Venue

  • Deep Learning Training Level 1: 22nd  April 2018 to 27th  April 2018
  • Venue: Charted Accountants House, 47 -49 Pearse Street, Dublin 2
  • Cost : €1,600


  • Details about the deep learning training courses based on the flyer content. Download brochure here.
  • Registration for this course is now closed.
  • Write to us for details at
  • Call us for details at +353 (0) 1 5291000