Teaching You To Solve Problems With Deep Learning

 

NVIDIA Deep Learning Institute (DLI) workshops, hosted by Boston, offer hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning.

Through self-paced labs and instructor-led workshops, the Deep Learning Institute teaches the latest techniques for designing, architecting, and deploying neural network-powered machine learning across a variety of application domains.

Students of the DLI will explore widely used open-source frameworks and NVIDIA’s latest GPU-accelerated deep learning platforms. Boston are pleased to be DLI Delivery Partners providing training globally. Whilst we organise several public courses through the year, and our trainers TA at GTC's across the world, Boston recommends Private Workshops for organisations, so that they may benefit from our trainers' expertise to tailor workshops to their requirements. 

 

 

Find the right course for you

 

DLI workshops teach you how to implement and deploy an end-to-end project in one day. These in-depth classes are taught by experts in their respective fields, delivering industry-leading technical knowledge to drive breakthrough results for individuals and organisations. We can tailor any course to suit your level of knowledge, be it beginner, intermediate or advanced.

 

Fundamentals of DL for Computer Vision

Train neural networks and solve problems with deep learning

DURATION: 8 Hours

FRAMEWORKS: Caffe, DIGITS

LANGUAGE: English, Japanese, Korean, Simplified/Traditional Chinese

PRE-REQUISITES: Familiarity with basic programming fundamentals

 

FUNDAMENTALS OF Deep Learning FOR NLP

Understand textual input using natural language processing (NLP)

DURATION: 20 Hours

FRAMEWORKS: TensorFlow, Keras

LANGUAGE: English, Chinese

PRE-REQUISITES: Basic experience with neural networks and Python programming, familiarity with linguistics

 

Fundamentals of Accelerated DL for Multi-GPUs

Use multiple GPUs to train neural networks and effectively parallelise training of deep neural networks using TensorFlow

FRAMEWORKS: TensorFlow

LANGUAGE: English

PRE-REQUISITES: Experience with stochastic-gradient-descent mechanics, network architecture and parallel computing

 

Fundamentals of Accelerated Computing with CUDA Python

Explore how to use Numba to accelerate Python programs to run of massively parallel NVIDIA GPUs

FRAMEWORKS: RAPIDS, NumPy, XGBoost, DBSCAN, K-Means, SSSP, Python

LANGUAGE: English

PRE-REQUISITES: Professional data science experience with Python, including proficiency in pandas and NumPy. Familiarity with XGBoost, DBSCAN, K-Means and SSSP

 

Fundamentals of Deep Learning Computing with CUDA

Accelerate & optimise C/C++ CPU- only apps using CUDA

DURATION: 8 Hours

FRAMEWORKS: C/C++, CUDA

LANGUAGE: English, Korean, Traditional Chinese

PRE-REQUISITES: Basic C/C++ competency, Assuming no previous knowledge of CUDA programming

 

Fundamentals of Accelerated DL for Multiple Data Types

Train convolutional & recurrent neural networks to generate captions from images & video using TensorFlow and the Microsoft Common Objects in Context (COCO) data set

FRAMEWORKS: TensorFlow

LANGUAGE: Japanese, Korean, Traditional Chinese

PRE-REQUISITES: Familiarity with basic Python and prior experience with training neural networks

 

Deep Learning for Autonomous Vehicles

Design, train and deploy deep neural networks and optimise perception components for autonomous vehicles using the NVIDIA DRIVE™ development platform

FRAMEWORKS: TensorFlow, NVIDIA TensorRT™, Python, NVIDIA CUDA C++, DIGITS

LANGUAGE: English, Simplified Chinese

PRE-REQUISITES: Experience with CNNs and C++

 

Deep Learning for Healthcare Image Analysis

Learn how to apply CNNs to MRI scans to perform a variety of medical tasks & calculations

FRAMEWORKS: R, MXNet, TensorFlow, Caffe, DIGITS

LANGUAGE: English

PRE-REQUISITES: Basic familiarity with deep neural networks and basic coding experience in Python or similar language

 

Fundamentals of Accelerated Data Science with RAPIDS

Perform multiple analysis tasks using RAPIDS, a collection of data science libraries allowing end-to-end GPU acceleration for data science workflows

FRAMEWORKS: RAPIDS, NumPy, XGBoost, DBSCAN, K-Means, SSSP, Python

LANGUAGE: English

PRE-REQUISITES: Professional data science experience with Python. Familiarity with common ML algorithms

 

 

Boston Training Academy

 

The mission of the Boston Training Academy (BTA) is to become a renowned developmental ground for talent engagement, education and solutions across a variety of disciplines. The BTA offers structured, face-to-face, labs and training delivered by world-class trainers that are tailored to the knowledge-base of the attendees. For a range of other courses, please visit the Boston Training Academy.

The Boston Training Academy (BTA) is pleased to launch LIVE and Fully Interactive instructor-led learning, presented by leading industry expert trainers with practical labs at your desk - so no need to travel or change your schedule!

 

FIND OUT MORE

Test out any of our solutions at Boston Labs

To help our clients make informed decisions about new technologies, we have opened up our research & development facilities and actively encourage customers to try the latest platforms using their own tools and if necessary together with their existing hardware. Remote access is also available

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