Nu hos CGit: NVIDIA DLI Hands-On Training!

12 månader sedan

CGit kommer från och med idag att erbjuda lärarledda workshops i samarbete med NVIDIA. Dessa workshops är endagarskurser (8 timmar) där hands-on-träning varvas med föreläsningar som levereras av DLI-certifierade instruktörer.

NVIDIA’s “Deep Learning Institute” (DLI) tränar utvecklare, data-scientists, och forskare i hur man använder artificiell intelligens och accelererad beräkning för att lösa verkliga problem inom en mängd olika områden.

På deep-learning kurserna kommer du lära dig att träna, optimera och driftsätta neurala nätverk. I kurserna som berör accelererad beräkning kommer du lära dig att bedöma, parallellisera, optimera och driftsätta GPU-accelererade applikationer.

Vi kan genomföra kurserna på valfri ort och med ett maximalt antal deltagare om 20 personer per tillfälle. Alla kurser sker på engelska. Kursstart sker tidigast 6 veckor efter bokning.

 

Nedan finner du exempel på lärarledda kurser. Är du intresserad av hela utbudet, ta kontakt med oss så berättar vi mer.

 

”Fundamentals of Deep Learning for Computer vision”

Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities. Learn how to start solving problems with deep learning.

Prerequisites: None

Frameworks: Caffe

 

“Fundamentals of Deep Learning for Natural Language Processing”

Explore the latest techniques for understanding textual input using natural language processing (NLP). You’ll learn how to convert text to machine understandable representation and train Machine Translators from one language to another.

Prerequisites: Basic experience with neural networks

Frameworks: TensorFlow, Keras

 

Fundamentals of Deep Learning for Multi-GPUs

Learn how to use multiple GPUs to train neural networks and effectively parallelise training of deep neural networks using TensorFlow

Prerequisites: Experience with stochastic gradient descent mechanics

Frameworks: TensorFlow

 

Branschsfokuserade kurser

 

Deep Learning for Autonomous Vehicles – Perception

Learn how to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE PX development platform. Create and optimize perception components for autonomous vehicles using NVIDIA DRIVE PX.

Prerequisites: Experience with CNNs

Frameworks: TensorFlow, DIGITS, TensorRT

 

Deep Learning for Finance Trading Strategy

Finance trading strategies can be advanced with the power of deep neural networks. Learn how to use time series financial data to make predictions and exploit arbitrage using neural networks.

Prerequisites: Experience with neural networks and knowledge of the financial industry

Frameworks: TensorFlow

 

Deep Learning for Digital Content Creation with Autoencoders

Learn how to animate characters with phase-function neural networks, explore techniques to make arbitrary photo and video style transfer, and train your won denoiser for rendered images.

Prerequisites: Experience with CNNs

Frameworks: Torch, TensorFlow

 

Deep Learning for Healthcare image Analysis

Learn how to apply convolutional neural networks (CNNs) to MRI scans to perform a variety of medical tasks and calculations.

Prerequisites: Basic Experience with CNNs and Python

Frameworks: Caffe, DIGITS, MXNet, TensorFlow

 

Deep Learning for Healthcare Genomics

Learn how convolutional neural networks (CNNs) work and how to apply deep learning to detect chromosome co-deletion and search for motifs in genomic sequences.

Prerequisites: Basic Experience with CNNs and Python

Frameworks: Caffe, TensorFlow, Theano