NVIDIA Deep Learning Institute Artificial Intelligence 3-Days Workshop SeriesRegister Now

    • Description

      Artificial Intelligence (AI), and Deep learning (DL) in particular, is transforming every industry. With major breakthroughs in computer vision, natural language processing, speech recognition and autonomous driving, deep learning has become the hottest topic in Artificial Intelligence. We have reached a crucial moment where deep learning and high performance computing are converging to deliver on promises made by big data. In this workshop series, we will explore the fundamentals of deep learning and discuss the current trend of this fast moving field, including the latest on various DL software frameworks and HPC hardware/cloud platforms. Following the success stories of applying deep learning to computer vision, natural language processing, and multiple data types, course participants will gain hands-on experience training deep neural networks and using results to improve performance and capabilities. Upon completion, attendees will be able to solve their own problems with deep learning. Participants will also receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

    • Benefits
      This workshop series is designed to empower you to jumpstart AI and gain the needed hands-on skills and expertise to leverage this technology in order to solve the world’s most challenging problems.
      • Learn to build deep learning applications for industries such as autonomous vehicles, finance, game development, healthcare, robotics, and more.
      • Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
      • Gain real-world expertise through content designed by NVIDIA Deep Learning Institute.
      • Earn an NVIDIA DLI certificate to demonstrate your subject matter competency and support career growth.
      • Access content anywhere, anytime with a fully configured, GPU-accelerated workstation in the cloud.
    • Learning Outcome
      In this workshop series, participants will learn the basics of deep learning by training and deploying neural networks, building the skill-set and toolbox they need to design their own deep learning solutions through hands-on projects. Participants will:
      • Understand general terms and background of deep learning
      • Implement common deep learning workflows such as Image Classification and Object Detection on the latest HPC platforms
      • Manipulate training parameters to improve accuracy
      • Modify internal layers of neural networks to adapt to new problems
      • Deploy their networks to start solving real-world problems
      • Learn how to train convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to generate captions from images and video using TensorFlow and the Microsoft Common Objects in Context (COCO) dataset
      • Explore how to convert text to machine understandable representation and train Machine Translators from one language to another using natural language processing (NLP)
    • Who Is This Training Designed For
      • Fresh Graduates entering the job market.
      • Developers who aim to learn today’s most sought after skill
      • Software Engineers who seek to advance their careers with the state-of the art AI expertise
      • Data Scientists and researchers who want to solve challenging problems with AI
      • Technology leaders who want to stay ahead of the competition by empowering their companies with AIms
      • IT consultants
      • Digital Transformation Specialists
    • Outline of the Workshop Series
      This workshop series will be conducted over three days via NVIDIA’s DLI virtual classroom environment using an online training platform that leverages supercomputing resources in the cloud.

      Day 1: Fundamentals of Deep Learning for Computer Vision

      This workshop teaches deep learning techniques for a range of computer vision tasks. After an introduction to deep learning, students advance to building and deploying deep learning applications for image classification and object detection, modifying your neural networks to improve their accuracy and performance, and implementing the techniques they’ve learned on a final project. At the end of this module, students have access to additional resources to create new deep learning applications on your own.

      Topics:
      • Join the account at courses.nvidia.com/join
      • Learn the biological inspiration behind deep neural networks (DNNs).
      • Explore training DNNs with big data.
      • Train neural networks to perform image classification by harnessing the three main ingredients of deep learning: deep neural networks, big data, and the GPU.
      • Deploy trained neural networks from their training environment into real applications.
      • Optimize DNN performance.
      • Incorporate object detection into your DNNs.
      • Validate learnings by applying the deep learning application development workflow (load dataset, train, and deploy model) to a project.
      • Learn how to set up your GPU-enabled environment to begin work on your own projects.
      • Explore additional project ideas and resources to get started with NVIDIA AMI in the cloud, nvidia-docker, and the NVIDIA DIGITS container.

      *Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.


      Day 2: Fundamentals of Deep Learning for Multiple Data Types

      This workshop uses a series of hands-on exercises to teach deep learning techniques for a range of problems involving multiple data types. Students advance to building deep learning applications for image segmentation, sentence generation, and image and video captioning, while learning relevant computer vision, neural network, and natural language processing concepts. At the end of this workshop, students will be able to assess a broad spectrum of problems where deep learning can be applied. The tools that are used TensorFlow and TensorBoard.

      Topics:
      • Join the account at courses.nvidia.com/join
      • Compare image segmentation to other computer vision problems.
      • Experiment with TensorFlow tools.
      • Implement effective metrics for assessing model performance.
      • Learn about natural language processing (NLP) and recurrent neural networks (RNNs).
      • Create network inputs from text data.
      • Test with new data and iterate to improve performance.
      • Combine computer vision and natural language processing to describe scenes.
      • Learn to harness the functionality of convolutional neural networks (CNNs) and RNNs.

      *Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

      Day 3: Fundamentals of Deep Learning for Natural Language Processing

      This workshop teaches deep learning techniques for understanding textual input using natural language processing (NLP) through a series of hands-on exercises. Students will learn techniques to train a neural network for text classification, build a linguistic style model to extract features from a given text document, and create a neural machine translation model for converting text from one language to another. The tools used are TensorFlow and Keras.

      Topics:
      • Join the account at courses.nvidia.com/join
      • Explore the importance of data representation for computers to understand language, as well as NLP challenges and how to tackle them with deep learning.
      • Learn about distributed data representations, such as word embeddings, using the Word2Vec algorithm. Once trained, word embeddings can be used for text classification.
      • Build a linguistic style model to extract features from a given set of texts using embeddings.
      • Use text classification to determine the authors of an unknown set of documents.
      • Create a neural machine translation model to convert text from one language to another.
      • Learn the basic technique to translate human-readable text to machine- readable format.
      • Use attention mechanisms to improve results—especially for long strings.

      *Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

    • This hands-on workshop series is brought to you in collaboration with NVIDIA Deep Learning Institute and AI Lab.
    • About
      NVIDIA Deep Learning Institute

      The NVIDIA Deep Learning Institute (DLI) trains developers, data scientists, and researchers on how to use deep learning and accelerated computing to solve real-world problems across a wide range of domains. With access to GPU-accelerated workstations in the cloud, you’ll learn how to train, optimize, and deploy neural networks using the latest deep learning tools, frameworks, and SDKs. You’ll also learn how to assess, parallelize, optimize, and deploy GPU-accelerated computing applications.


      AI LAB

      AI Lab is the official delivery partner of NVIDIA Deep Learning Institute (DLI) in EMEA. The NVIDIA Deep Learning Institute (DLI) trains developers, data scientists, and researchers on how to use deep learning and accelerated computing to solve real-world problems across a wide range of domains. Through this partnership, AL Lab delivers NVIDIA DLI’s trainings and hands-on workshops for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing.

    • About the Facilitators

      Dr. Manal Jalloul is a lecturer and researcher at the American University of Beirut. Her research interests lie in the fields of digital image and video processing, 3D printing, parallel computing, and artificial intelligence. She has several peer-reviewed publications in international journals and conferences. She is also a research consultant for two emerging tech startups where she is developing state-of the art software for 3D printing and applying deep learning algorithms for counterfeit applications. She is a certified instructor and University ambassador at Nvidia’s Deep Learning Institute (DLI). She is also the co-founder of AI-Lab, which is the certified partner of NVIDIA in EMEA. AI Lab aims to provide specialized hands-on trainings and consulting services in the fields of Artificial Intelligence, Accelerated Computing, and Data Analytics to the industry in the region.


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Highlights

  • Learn to build deep learning applications for industries such as autonomous vehicles, finance, game development, healthcare, robotics, and more.
  • Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
  • Gain real-world expertise through content designed by NVIDIA Deep Learning Institute.
  • Earn an NVIDIA DLI certificate to demonstrate your subject matter competency and support career growth.
  • Access content anywhere, anytime with a fully configured, GPU-accelerated workstation in the cloud.
Course Date: 3 days on September 19, 26, and Oct 3
Duration: 9 AM - 5 PM with one hour break
(time zone: UTC+4)
Place: Online
Fee: AED 5515.00 (Excluding VAT)

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CEPPS
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American University in Dubai
PO Box: 28282

(+971)4 318 3117

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