NVIDIA DLI AMBASSADOR WORKSHOP SERIES

FREE, HANDS-ON,
INSTRUCTOR LED TRAINING

NVIDIA Deep Learning Institute (DLI) is collaborating with NVIDIA DLI Certified Instructors to deliver workshops that are delivered remotely through a virtual classroom FREE of cost for Faculty and Students.

The workshops will be conducted by volunteer DLI Certified Instructors (NVIDIA DLI University Ambassadors)

QUICK TIPS FOR FACULTY AND STUDENTS

  • These free workshops are only open to faculty and students from accredited educational institutions.
  • You’ll need a valid school ID and email ID to register, preferably with an .ac or .edu domain.
  • Seats for each workshops are limited and will be allotted based on the registration details provided.
  • Each workshop has its own requirements, so please review them to ensure that you qualify.
  • These are full-day ‘hands-on’ workshops that require a computer (laptop/desktop) and a broadband internet connection to participate.
Deep Learning Institute Virtual Workshops

CHOOSE YOUR WORKSHOP AND REGISTER

Workshop dates: 31/07, TBD

Fundamentals of Deep Learning

Learn how deep learning works through hands-on exercises in CV & NLP over this course…

See more info >

Workshop dates: 01/08, TBD

Building Transformer-Based Natural Language Processing Applications

Explore with hands on lab's, Transformer-based NLP models for text classification tasks like categorizing documents in this workshop…

See more info >

Workshop dates: TBD

Fundamentals of Accelerated Data Science

Learn how to build and execute end-to-end GPU-accelerated data science workflows that enable you to quickly explore, iterate, and get your work into production in this workshop…

See more info >
REGISTER
Deep Learning Institute Virtual Workshops

JOIN THE NVIDIA DLI UNIVERSITY AMBASSADOR PROGRAM

The DLI University Ambassador Program gives qualified educators everything they need to teach DLI workshops to faculty, students, and researchers across campuses and academic conferences—all at no cost.

If you’re a faculty and qualified instructor with expertise in deep learning and accelerated computing and want to be a DLI Certified Instructor and Ambassador, apply today.

APPLY

Available dates: 31/07, TBD

Fundamentals of Deep Learning

Learn how deep learning works through hands-on exercises in CV & NLP over this course. In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. In this workshop, you’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.

By participating in this workshop, you’ll:

  • Learn the fundamental techniques and tools required to train a deep learning model
  • Gain experience with common deep learning data types and model architectures
  • Enhance datasets through data augmentation to improve model accuracy
  • Leverage transfer learning between models to achieve efficient results with less data and computation
  • Build confidence to take on your own project with a modern deep learning framework.

Prerequisites: 
An understanding of fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and an understanding of how to compute a regression line.

Technologies: 
Tensorflow 2 with Keras, Pandas.

Certificate: Yes.

View Datasheet

Available dates: 01/08, TBD

Building Transformer-Based Natural Language Processing Applications

Explore with hands on lab's, Transformer-based NLP models for text classification tasks like categorizing documents in this workshop. You’ll also learn how to leverage Transformer-based models for named-entity recognition (NER) tasks and how to analyze various model features, constraints, and characteristics to determine which model is best suited for a particular use case based on metrics, domain specificity, and available resources.

By participating in this workshop, you’ll:

  • Understand how text embeddings have rapidly evolved in NLP tasks such as Word2Vec, recurrent neural network (RNN)-based embeddings, and Transformers
  • See how Transformer architecture features, especially self-attention, are used to create language models without RNNs
  • Use self-supervision to improve the Transformer architecture in BERT, Megatron, and other variants for superior NLP results
  • Leverage pre-trained, modern NLP models to solve multiple tasks such as text classification, NER, and question answering
  • Manage inference challenges and deploy refined models for live applications

Prerequisites:

  • Experience with Python coding and use of library functions and parameters
  • Fundamental understanding of a deep learning framework such as TensorFlow, PyTorch, or Keras
  • Basic understanding of neural networks

Suggested materials to satisfy prerequisites:
Python Tutorial, Overview of Deep Learning Frameworks, PyTorch Tutorial, Deep Learning in a Nutshell, Deep Learning Demystified

Technologies: 
PyTorch, pandas, NVIDIA NeMo™, NVIDIA Triton™ Inference Server

View Datasheet

Please select the required Workshop and respective Date and register.

Workshop
Name
Workshop
Date
Course
Instructor
Registration
Link
Fundamentals of Deep Learning
July 31st 2021
Dr. Priyanka Sharma | DLI Ambassador
Building Transformer-Based Natural Language Processing Applications
August 1st 2021
Dr. Priyanka Sharma | DLI Ambassador

Note

  • Register for each workshop separately. Please choose only one date per workshop.
  • Please prepare for the workshop by creating an NVIDIA account, testing your laptop, and carefully reviewing the course datasheet to become familiar with Prerequisites, Learning Objectives, and Agenda Outline. Refer details at https://developer.nvidia.com/dli/getready and follow instructions there in.
  • NVIDIA DLI Ambassador Workshop is being offered FREE of cost ($500 value per WS) for Faculty & Students.The registrations are accepted based on details submitted with preferenace for regsitrations with Institute email ID's. There are limited seats for each workshop and these are allottted on First cum First served basis.

Available dates: TBD

Fundamentals of Accelerated Data Science

Learn how to build and execute end-to-end GPU-accelerated data science workflows that enable you to quickly explore, iterate, and get your work into production in this workshop. Using the RAPIDS™-accelerated data science libraries, you’ll apply a wide variety of GPU-accelerated machine learning algorithms, including XGBoost, cuGRAPH’s single-source shortest path, and cuML’s KNN, DBSCAN, and logistic regression to perform data analysis at scale.

By participating in this workshop, you’ll:

  • Implement GPU-accelerated data preparation and feature extraction using cuDF and Apache Arrow data frames
  • Apply a broad spectrum of GPU-accelerated machine learning tasks using XGBoost and a variety of cuML algorithms
  • Execute GPU-accelerated graph analysis with cuGraph, achieving massive-scale analytics in small amounts of time
  • Rapidly achieve massive-scale graph analytics using cuGraph routines

Prerequisites:
Experience with Python, ideally including pandas and NumPy

Suggested resources to satisfy prerequisites:
Kaggle's pandas Tutorials, Kaggle's Intro to Machine Learning, Accelerating Data Science Workflows with RAPIDS

Technologies: 
RAPIDS, cuDF, XGBoost, cuML, cuGraph, Dask, cuPy, pandas, NumPy, Bokeh

View Datasheet
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