Hands-on training on AI and CUDA in CET timezone

It’s a thread with all upcoming NVIDIA Deep learning Institute trainings in EMEA timezone

Nov 9, 2022, online: Applications of AI for Anomaly Detection (EMEA)
Whether your organization needs to monitor cybersecurity threats, fraudulent financial transactions, product defects, or equipment health, artificial intelligence can help catch data abnormalities before they impact your business. AI models can be trained and deployed to automatically analyze datasets, define “normal behavior,” and identify breaches in patterns quickly and effectively. These models can then be used to predict future anomalies. With massive amounts of data available across industries and subtle distinctions between normal and abnormal patterns, it’s critical that organizations use AI to quickly detect anomalies that pose a threat.

In this workshop, you’ll learn how to implement multiple AI-based approaches to solve a specific use case of identifying network intrusions for telecommunications. You’ll learn three different anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques. At the end of the workshop, you’ll be able to use AI to detect anomalies in your work across telecommunications, cybersecurity, finance, manufacturing, and other key industries.

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Nov 10, 2022, online: Fundamentals of Accelerated Computing with CUDA C/C++ (EMEA)
This workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA®. You’ll learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that you’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. At the end of the workshop, you’ll have access to additional resources to create new GPU-accelerated applications on your own.

Nov 8, 2022, online: Model Parallelism: Building and Deploying Large Neural Networks (EMEA)
Very large deep neural networks (DNNs), whether applied to natural language processing (e.g., GPT-3), computer vision (e.g., huge Vision Transformers), or speech AI (e.g., Wave2Vec 2) have certain properties that set them apart from their smaller counterparts. As DNNs become larger and are trained on progressively larger datasets, they can adapt to new tasks with just a handful of training examples, accelerating the route toward general artificial intelligence. Training models that contain tens to hundreds of billions of parameters on vast datasets isn’t trivial and requires a unique combination of AI, high-performance computing (HPC), and systems knowledge. The goal of this course is to demonstrate how to train the largest of neural networks and deploy them to production.

Hands-on training at Transform
DevRain Transform is an annual online event for software developers, data scientists, and ML engineers happening on Nov 28-Dec 6. Update your knowledge with applied AI technologies, use cases, best practices and news from top experts.
Register now and sharpen your skills at NVIDIA DLI workshops. Be quick, seats are limited.
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For Students Attending the Global AI Student Conference

In addition to hearing from great educators on AI projects and technologies, you’ll be able to attend a full-day workshop “Fundamentals of Deep Learning” on Dec 14th for free, and earn a certificate after completing the assessment. The amount of seats is limited, so don’t delay in registering.
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**Jan18th, 2023, online: Computer Vision for Industrial Inspection
Whether companies are manufacturing semiconductor chips, airplanes, automobiles, smartphones, or food or beverages, quality and throughput are key benefits of optimization. Poor quality and throughput can result in significant operational, financial, and reputational costs. Deep learning-based computer vision technology enables manufacturers to perform automated visual inspection. Compared to traditional visual inspection processes—which are often manual and rules-based—visual inspection AI can improve efficiency, reduce operating costs, and deliver more consistent results.

In this Deep Learning Institute (DLI) workshop, developers will learn how to create an end-to-end hardware-accelerated industrial inspection pipeline to automate defect detection. Using NVIDIA’s own real production data set as an example, we’ll illustrate how the application can be easily applied to a variety of manufacturing use cases. Developers will also learn to identify and mitigate common pitfalls in deep learning-based computer vision tasks, and be able to deploy and measure the effectiveness of their AI solution.

All workshop attendees get access to fully configured, GPU-accelerated servers in the cloud, guidance from a DLI certified instructor, and the opportunity to network with other developers, data scientists, and researchers attending the workshop. Attendees can also earn a certificate to prove subject matter competency and support professional growth.
Register here