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 buildin...
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.
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 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.
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 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 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 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.
For those who want to start with new software as well as who already know other software for vector graphics and want to quickly start working with new software.
During the 3-day training, participants will learn a bit of history of theory and guidelines converted into example projects:
"Scribing" from a drawing on paper to a vector image that can be used for printing, cutting, engraving, etc.
"Pierre Bézier curves" rules for creating basic curves and complex curves as well as editing and repairing.
"Typography" creating your own font from drawing to obtaining an open type font (OTF) file.
Adobe graphics programs are 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 This 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.
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 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.
FreeCAD is an open-source, customizable, multi-platform, scriptable and extensible parametric 3D modeler for designing real-life objects.
In this instructor-led, live training, participants will learn how to model an object for later construction or 3D printing.
By the end of this training, participants will be able to:
Use FreeCad's tools and workflows to replace commercial CAD or BIM modeling software
Write to many formats such as STEP, IGES, STL, SVG, DXF, OBJ, IFC, DAE, etc.
Use Python to extend FreeCAD's functionality
Automate FreeCad, build modules and embed FreeCAD into an existing application
Audience
Designers
Developers
Mechanical engineers
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).
This course covers how to program GPUs for parallel computing. Some of the applications include deep learning, analytics, and engineering applications.
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.
This instructor-led, live training in Connecticut (online or onsite) is aimed at developers who wish to build hardware-accelerated object detection and tracking models to analyze streaming video data.
By the end of this training, participants will be able to:
Install and configure the necessary development environment, software and libraries to begin developing.
Build, train, and deploy deep learning models to analyze live video feeds.
Identify, track, segment and predict different objects within video frames.
Optimize object detection and tracking models.
Deploy an intelligent video analytics (IVA) application.
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 web designers who wish to use Maya for creating 3D animations.
By the end of this training, participants will be able to:
Create realistic models and textures in Maya.
Animate and render projects for high quality playback.
This instructor-led, live training in Connecticut (online or onsite) is aimed at 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.
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Testimonials (4)
Everything was done at a perfectly adjusted pace in an understandable and accessible way, enabling effective learning and expanding one's competences. The trainer is a qualified person who can explain many issues in order to improve the projects completed during the course. Using simple examples, it shows and analyzes important aspects that are needed to create more advanced models. I consider the training to be very successful.
Klaudia - CB POLAND sp. z o.o.
Course - Blender: 3D Modeling Fundamentals
Machine Translated
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
La dinamica.
Miguel Angel Hernandez Cardenas - KNOW COACHING HOW S.C.
Course - Adobe LiveCycle Designer
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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