Online or onsite, instructor-led live Computer Graphics training courses demonstrate through interactive discussion and hands-on practice the fundamentals of Computer Graphics.
Computer Graphics training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Connecticut onsite live Computer Graphics trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
CT, Shelton - Shelton
One Reservoir Corporate Center, 4 Research Dr Suite 402, Shelton, United States, 06484
One Reservoir Corporate Center is a prestigious business address in the heart of Shelton office park area, and the building has a well-appointed reception area. The building is on a prominent corner plot and overlooks landscaped green space.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use OpenACC to program heterogeneous devices and exploit their parallelism.
By the end of this training, participants will be able to:
Set up an OpenACC development environment.
Write and run a basic OpenACC program.
Annotate code with OpenACC directives and clauses.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to learn the basics of GPU programming and the main frameworks and tools for developing GPU applications.
By the end of this training, participants will be able to: Understand the difference between CPU and GPU computing and the benefits and challenges of GPU programming.
Choose the right framework and tool for their GPU application.
Create a basic GPU program that performs vector addition using one or more of the frameworks and tools.
Use the respective APIs, languages, and libraries to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
Use the respective memory spaces, such as global, local, constant, and private, to optimize data transfers and memory accesses.
Use the respective execution models, such as work-items, work-groups, threads, blocks, and grids, to control the parallelism.
Debug and test GPU programs using tools such as CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
Optimize GPU programs using techniques such as coalescing, caching, prefetching, and profiling.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use different frameworks for GPU programming and compare their features, performance, and compatibility.
By the end of this training, participants will be able to:
Set up a development environment that includes OpenCL SDK, CUDA Toolkit, ROCm Platform, a device that supports OpenCL, CUDA, or ROCm, and Visual Studio Code.
Create a basic GPU program that performs vector addition using OpenCL, CUDA, and ROCm, and compare the syntax, structure, and execution of each framework.
Use the respective APIs to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
Use the respective languages to write kernels that execute on the device and manipulate data.
Use the respective built-in functions, variables, and libraries to perform common tasks and operations.
Use the respective memory spaces, such as global, local, constant, and private, to optimize data transfers and memory accesses.
Use the respective execution models to control the threads, blocks, and grids that define the parallelism.
Debug and test GPU programs using tools such as CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
Optimize GPU programs using techniques such as coalescing, caching, prefetching, and profiling.
CloudMatrix is Huawei’s unified AI development and deployment platform designed to support scalable, production-grade inference pipelines.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level AI professionals who wish to deploy and monitor AI models using the CloudMatrix platform with CANN and MindSpore integration.
By the end of this training, participants will be able to:
Use CloudMatrix for model packaging, deployment, and serving.
Convert and optimize models for Ascend chipsets.
Set up pipelines for real-time and batch inference tasks.
Monitor deployments and tune performance in production settings.
Format of the Course
Interactive lecture and discussion.
Hands-on use of CloudMatrix with real deployment scenarios.
Guided exercises focused on conversion, optimization, and scaling.
Course Customization Options
To request a customized training for this course based on your AI infrastructure or cloud environment, please contact us to arrange.
This instructor-led, live training in Connecticut (online or onsite) is aimed at artists, game developers, or complete beginners who wish to use Blender to create 3D models for interactive applications, video games, animated films, etc.
By the end of this training, participants will be able to:
Learn how to create animations and visual effects with Blender.
Add curves, surfaces, metaballs, and hair particles to simulate realistic 3D motions.
Introduction to non-destructive modelling and animation.
Export 3D models and assets to a game engine, 3D printer, or other software.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to install and use ROCm on Windows to program AMD GPUs and exploit their parallelism.
By the end of this training, participants will be able to:
Set up a development environment that includes ROCm Platform, a AMD GPU, and Visual Studio Code on Windows.
Create a basic ROCm program that performs vector addition on the GPU and retrieves the results from the GPU memory.
Use ROCm API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
Use HIP language to write kernels that execute on the GPU and manipulate data.
Use HIP built-in functions, variables, and libraries to perform common tasks and operations.
Use ROCm and HIP memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
Use ROCm and HIP execution models to control the threads, blocks, and grids that define the parallelism.
Debug and test ROCm and HIP programs using tools such as ROCm Debugger and ROCm Profiler.
Optimize ROCm and HIP programs using techniques such as coalescing, caching, prefetching, and profiling.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use ROCm and HIP to program AMD GPUs and exploit their parallelism.
By the end of this training, participants will be able to:
Set up a development environment that includes ROCm Platform, a AMD GPU, and Visual Studio Code.
Create a basic ROCm program that performs vector addition on the GPU and retrieves the results from the GPU memory.
Use ROCm API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
Use HIP language to write kernels that execute on the GPU and manipulate data.
Use HIP built-in functions, variables, and libraries to perform common tasks and operations.
Use ROCm and HIP memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
Use ROCm and HIP execution models to control the threads, blocks, and grids that define the parallelism.
Debug and test ROCm and HIP programs using tools such as ROCm Debugger and ROCm Profiler.
Optimize ROCm and HIP programs using techniques such as coalescing, caching, prefetching, and profiling.
This instructor-led, live training in Connecticut (online or onsite) is aimed at artists, game developers, or complete beginners who wish to use Blender to create 3D models for interactive applications, video games, animated films, etc.
By the end of this training, participants will be able to:
Understand the principles and core concepts of 3D modeling.
Explore a variety of modes and tools for modeling and editing 3D meshes.
Use the tools for UV mapping/unwrapping, sculpting, and painting 3D models renderring.
Ascend, Biren, and Cambricon are leading AI hardware platforms in China, each offering unique acceleration and profiling tools for production-scale AI workloads.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI infrastructure and performance engineers who wish to optimize model inference and training workflows across multiple Chinese AI chip platforms.
By the end of this training, participants will be able to:
Benchmark models on Ascend, Biren, and Cambricon platforms.
Identify system bottlenecks and memory/compute inefficiencies.
Apply graph-level, kernel-level, and operator-level optimizations.
Tune deployment pipelines to improve throughput and latency.
Format of the Course
Interactive lecture and discussion.
Hands-on use of profiling and optimization tools on each platform.
Guided exercises focused on practical tuning scenarios.
Course Customization Options
To request a customized training for this course based on your performance environment or model type, please contact us to arrange.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level graphic designers and animators who wish to learn how to create stunning animations, interactive media, and engaging web content using Adobe Animate.
By the end of this training, participants will be able to:
Navigate the Adobe Animate interface and tools.
Create and edit animations using keyframes, motion tweens, and shape tweens.
Design interactive animations and applications with ActionScript and JavaScript.
Incorporate audio and video elements into projects.
Export animations for web, video, and mobile platforms.
Chinese GPU architectures such as Huawei Ascend, Biren, and Cambricon MLUs offer CUDA alternatives tailored for local AI and HPC markets.
This instructor-led, live training (online or onsite) is aimed at advanced-level GPU programmers and infrastructure specialists who wish to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.
By the end of this training, participants will be able to:
Evaluate compatibility of existing CUDA workloads with Chinese chip alternatives.
Port CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
Compare performance and identify optimization points across platforms.
Address practical challenges in cross-architecture support and deployment.
Format of the Course
Interactive lecture and discussion.
Hands-on code translation and performance comparison labs.
Guided exercises focused on multi-GPU adaptation strategies.
Course Customization Options
To request a customized training for this course based on your platform or CUDA project, please contact us to arrange.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use CUDA to program NVIDIA GPUs and exploit their parallelism.
By the end of this training, participants will be able to:
Set up a development environment that includes CUDA Toolkit, a NVIDIA GPU, and Visual Studio Code.
Create a basic CUDA program that performs vector addition on the GPU and retrieves the results from the GPU memory.
Use CUDA API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
Use CUDA C/C++ language to write kernels that execute on the GPU and manipulate data.
Use CUDA built-in functions, variables, and libraries to perform common tasks and operations.
Use CUDA memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
Use CUDA execution model to control the threads, blocks, and grids that define the parallelism.
Debug and test CUDA programs using tools such as CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
Optimize CUDA programs using techniques such as coalescing, caching, prefetching, and profiling.
Huawei Ascend is a family of AI processors designed for high-performance inference and training.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI engineers and data scientists who wish to develop and optimize neural network models using Huawei’s Ascend platform and the CANN toolkit.
By the end of this training, participants will be able to:
Set up and configure the CANN development environment.
Develop AI applications using MindSpore and CloudMatrix workflows.
Optimize performance on Ascend NPUs using custom operators and tiling.
Deploy models to edge or cloud environments.
Format of the Course
Interactive lecture and discussion.
Hands-on use of Huawei Ascend and CANN toolkit in sample applications.
Guided exercises focused on model building, training, and deployment.
Course Customization Options
To request a customized training for this course based on your infrastructure or datasets, please contact us to arrange.
Biren AI Accelerators are high-performance GPUs designed for AI and HPC workloads with support for large-scale training and inference.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level developers who wish to program and optimize applications using Biren’s proprietary GPU stack, with practical comparisons to CUDA-based environments.
By the end of this training, participants will be able to:
Understand Biren GPU architecture and memory hierarchy.
Set up the development environment and use Biren’s programming model.
Translate and optimize CUDA-style code for Biren platforms.
Apply performance tuning and debugging techniques.
Format of the Course
Interactive lecture and discussion.
Hands-on use of Biren SDK in sample GPU workloads.
Guided exercises focused on porting and performance tuning.
Course Customization Options
To request a customized training for this course based on your application stack or integration needs, please contact us to arrange.
This instructor-led, live training in Connecticut (online or onsite) is aimed at artists, game developers, or complete beginners who wish to use Blender to create 3D models for interactive applications, video games, animated films, etc.
By the end of this training, participants will be able to:
Understand the principles and core concepts of 3D modeling.
Explore a variety of modes and tools for modeling and editing 3D meshes.
Learn how to create animations and visual effects with Blender.
Add curves, surfaces, metaballs, and hair particles to simulate realistic 3D motions.
Use the tools for UV mapping/unwrapping, sculpting, and painting 3D models.
Export 3D models and assets to a game engine, 3D printer, or other software.
Cambricon MLUs (Machine Learning Units) are specialized AI chips optimized for inference and training in edge and datacenter scenarios.
This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.
By the end of this training, participants will be able to:
Set up and configure the BANGPy and Neuware development environments.
Develop and optimize Python- and C++-based models for Cambricon MLUs.
Deploy models to edge and data center devices running Neuware runtime.
Integrate ML workflows with MLU-specific acceleration features.
Format of the Course
Interactive lecture and discussion.
Hands-on use of BANGPy and Neuware for development and deployment.
Guided exercises focused on optimization, integration, and testing.
Course Customization Options
To request a customized training for this course based on your Cambricon device model or use case, please contact us to arrange.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level system administrators and IT professionals who wish to install, configure, manage, and troubleshoot CUDA environments.
By the end of this training, participants will be able to:
Understand the architecture, components, and capabilities of CUDA.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use OpenCL to program heterogeneous devices and exploit their parallelism.
By the end of this training, participants will be able to:
Set up a development environment that includes OpenCL SDK, a device that supports OpenCL, and Visual Studio Code.
Create a basic OpenCL program that performs vector addition on the device and retrieves the results from the device memory.
Use OpenCL API to query device information, create contexts, command queues, buffers, kernels, and events.
Use OpenCL C language to write kernels that execute on the device and manipulate data.
Use OpenCL built-in functions, extensions, and libraries to perform common tasks and operations.
Use OpenCL host and device memory models to optimize data transfers and memory accesses.
Use OpenCL execution model to control the work-items, work-groups, and ND-ranges.
Debug and test OpenCL programs using tools such as CodeXL, Intel VTune, and NVIDIA Nsight.
Optimize OpenCL programs using techniques such as vectorization, loop unrolling, local memory, and profiling.
This instructor-led, live training in Connecticut (online or onsite) is aimed at designers, mechanical engineers, and anyone who wishes to learn how to create 3D models that can be constructed or 3D printed.
By the end of this training, participants will be able to:
Create printable 3D models.
Use geometric transformations to build complex 3D shapes.
Model in a non-interactive manner using minimal lines of code.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to advanced-level 3D design and 3D printing enthusiasts who wish to use Fusion 360 to design, simulate, and prepare models for 3D printing.
By the end of this training, participants will be able to:
Install and configure Fusion 360 for optimal performance.
Design, model, and simulate 3D objects in a unified environment.
Optimize and prepare designs for the 3D printing process.
Collaborate and share their designs using Fusion 360's cloud capabilities.
This instructor-led, live training in Connecticut (online or onsite) is aimed at beginner-level to intermediate-level developers and UI/UX designers who wish to use Adobe LiveCycle Designer to create interactive and dynamic PDF forms.
By the end of this training, participants will be able to:
Create and edit PDF forms with various elements and properties.
Add scripts and logic to PDF forms using JavaScript.
Validate and secure PDF forms.
Integrate PDF forms with data sources and web services.
This course is perfect for those who want to start their graphic design journey using Affinity Designer, one of the most popular and versatile vector graphics programs. If you are new to computer graphics and are looking for a solid foundation, this course will help you master the basic features and tools that are essential for creating professional designs, step by step.
During the course:
You will learn how to navigate the Affinity Designer interface, which will allow you to use its features with ease.
You will learn the basic tools for drawing and editing shapes, which will allow you to create your own illustrations and graphics.
You will understand how to work with layers and how to use colors and text in your designs.
You will master the basics of exporting your designs to different formats, ready for printing or publishing online.
After completing the course, you will be able to create simple graphics, logos, posters, and other visual materials using Affinity Designer tools. The course will provide you with a solid foundation that will allow you to further develop your graphic design skills.
ARToolKit is an open-source tracking library for creating Augmented Reality (AR) applications. It supports Windows, Linux, Mac, Android and iOS.
In this instructor-led, live training, participants will learn how to build an augmented reality mobile application with ARToolKit.
By the end of this training, participants will be able to:
Develop a mobile application that overlays virtual imagery onto the real world
Preprocess video to adjust lighting and resolve issues
Integrate ARToolKit with third-party tools and functionality, including OpenCV, Unity, OpenSceneGraph and the mobile device's GPS, compass, and camera calibration utilities
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
The mobile application developed in this course can be target Android and/or iOS. To request your preference, please contact us to arrange.
This instructor-led, live training in Connecticut (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.
By the end of this training, participants will be able to:
Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
Create, compile and launch custom CUDA kernels.
Manage GPU memory.
Convert a CPU based application into a GPU-accelerated application.
This instructor-led, live training course in Connecticut covers how to program GPUs for parallel computing, how to use various platforms, how to work with the CUDA platform and its features, and how to perform various optimization techniques using CUDA. Some of the applications include deep learning, analytics, image processing and engineering applications.
WebGL (Web Graphics Library) is a JavaScript API for rendering 3D graphics within a web browser without the use of plug-ins.
In this instructor-led, live training, participants will learn how to generate realistic computer images using 3D graphics as they step through the creation of an animated 3D application that runs in a browser.
By the end of this training, participants will be able to:
Understand and use WebGL's various functionality, including meshes, transforms, cameras, materials, lighting, and animation
Animate objects with WebGL
Create 3D objects using WebGL
Audience
Developers
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training in Connecticut (online or onsite) is aimed at design engineers, architects, and developers who wish to use Pixar USD to create, build, and share common 3D scenes or assets while working simultaneously from different graphics tools.
By the end of this training, participants will be able to:
Set up the necessary development environment to start building 3D graphics and workflows.
Understand the basic USD composition and apply modifications to enhance 3D assets and scenes.
Share, combine, and transform multiple assets using the supported USD plugins for 3rd party applications (Maya, Katana, and Houdini).
Graphics programs Adobe is a set of tools for creating, editing and manipulating graphics, multimedia and documents. Adobe Systems is known for creating many professional programs dedicated to graphics, multimedia, photo editing, website design and more. Here are some of the main graphics programs created by Adobe: Adobe Photoshop Jest is one of the most popular raster graphics editing programs. It allows you to manipulate photos, create graphics, retouch, color correction and many other advanced operations. Adobe Illustrator Focused on vector graphics, Illustrator lets you create logos, illustrations, vector graphics, typographic designs, and more that can be scaled without losing quality.
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Testimonials (5)
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.
Jenny - Andheo
Course - GPU Programming with CUDA and Python
Learning about the software
Peter - Coleg Cambria
Course - Blender: 3D Modeling Fundamentals
The dynamics.
Miguel Angel Hernandez Cardenas - KNOW COACHING HOW S.C.
Course - Adobe LiveCycle Designer
Machine Translated
Trainers energy and humor.
Tadeusz Kaluba - Nokia Solutions and Networks Sp. z o.o.
Course - NVIDIA GPU Programming - Extended
The trainer really targeted our need to a very specific case study and was able to adapt to the situation (as the solutions to our problematic evolved during the course), beyond the upstream preparation he did.
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