NVIDIA Training

Learning

Timing

Tech Light

Dr. Kris Manohar, UWI

Taurean Dyer, NVIDIA

Strategy

Njeri Wakins, QuantumLink

Dr. Mohammed Osman – Osman Analytics

Intro

Sunday:

1:00 PM – 4:00 PM

Joint AI Strategy and Enablement Master Class

Understanding some Fundamentals Foundations & Data Science

Monday Block 2:

1:40 PM – 3:00 PM

Customizing Gen AI

Monday Block 2:

3:10 PM – 4:30 PM

Deploying AI

Tuesday Block 4:

2:20 – 4:30+

Accelerate Data Science Workflows with Zero Code Changes

About this Course

Across industries, modern data science requires large amounts of data to be processed quickly and efficiently. These workloads need to be accelerated to ensure prompt results and increase overall productivity. NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes.

Learning Objectives

In this course, you’ll learn to use RAPIDS to speed up your CPU-based data science workflows. 

 

By participating in this workshop, you’ll:

  • Understand the benefits of a unified workflow across CPUs and GPUs for data science tasks.
  • Learn how to GPU-accelerate various data processing and machine learning workflows with zero code changes.
  • Experience the significant reduction in processing time when workflows are GPU-accelerated.

AI for All—From Basics to Gen AI Practice

Artificial Intelligence, or AI, is transforming society in many ways.  From speech recognition to self-driving cars, to the immense possibilities offered by generative AI. AI technology provides enterprises with the compute power, tools, and algorithms their teams need to do their life’s work. This introductory course provides invaluable insights into the evolving landscape of AI. Whether you’re a seasoned professional or just beginning your journey into AI, this course is essential for staying ahead in today’s rapidly evolving technological landscape. 

Augment your LLM Using Retrieval Augmented Generation

About this Course

Retrieval Augmented Generation (RAG) – Introduced by Facebook AI Research in 2020, is an architecture used to optimize the output of an LLM with dynamic, domain specific data without the need of retraining the model. RAG is an end-to-end architecture that combines an information retrieval component with a response generator. In this introduction we provide a starting point using components we at NVIDIA have used internally. This workflow will jumpstart you on your LLM and RAG journey.

Learning Objectives

  • Understand the basics of Retrieval Augmented Generation.
  • Learn about the RAG retreival process
  • Learn about NVIDIA AI Foundations and the components that constitue a RAG model.

Introduction to NVIDIA NIM™ Microservices

About this Course

NVIDIA NIM™ is a set of easy-to-use microservices designed for secure, reliable deployment of high performance AI model inferencing across the cloud, data center and workstations. It is designed to speed up AI deployment in enterprises, supporting various optimized community AI models. This Deep Learning Institute (DLI) course covers important concepts to help developers understand how NIM enables the building, deploying, and scaling of AI applications.

Learning Objectives

  • Describe the key features of NIM microservices
  • Perform self-hosted deployment of NIM microservices
  • Use NIM microservices to build an AI chatbot with retrieval-augmented generation (RAG)
  • Discover and explore innovative AI applications built with NIM microservices

Generative AI Explained

About this Course

Generative AI describes technologies that are used to generate new content based on a variety of inputs. In recent time, Generative AI involves the use of neural networks to identify patterns and structures within existing data to generate new content. In this course, you will learn Generative AI concepts, applications, as well as the challenges and opportunities in this exciting field.

Learning Objectives

Upon completion, you will have a basic understanding of Generative AI and be able to more effectively use the various tools built on this technology.