Delivered either online or onsite, our instructor-led live Computer Graphics training courses provide an interactive and hands-on environment where participants master the core principles of Computer Graphics through active discussion and practical application.
These programs are offered as either "online live training" or "onsite live training." The online option, also known as "remote live training," utilizes an interactive remote desktop connection to facilitate real-time collaboration. Onsite live training is conducted directly at customer premises in Plovdiv or within NobleProg corporate training centers located in Plovdiv.
NobleProg -- Your Local Training Provider
Business Center Plovdiv
Han Kubrat St 1, Plovdiv, Bulgaria, 4017
This is the most modern business center in the city, with all the necessary functionalities, while being located in a green part of the city.
It is about 20 minutes by bus from the main train station as well as the city center.
This instructor-led course in Plovdiv assists intermediate AI engineers in constructing and optimizing neural network models via the Huawei Ascend platform and CANN toolkit. Learners will set up environments, build applications using MindSpore, and manage deployment to edge or cloud settings.
This instructor-led live training in Plovdiv explores Huawei's AI stack, from the CANN SDK to the MindSpore framework. It helps beginners and intermediate professionals understand how these components integrate on Ascend hardware for lifecycle management and deployment.
This instructor-led, live training in Plovdiv (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 training in Plovdiv covers deploying and optimizing CV and NLP models using the CANN SDK for Ascend hardware. Participants will learn to convert models, integrate them into live pipelines, and enhance inference performance for real-time detection and analysis.
This instructor-led live training in Plovdiv (online or onsite) is tailored for beginner to intermediate-level developers who wish to understand the basics of GPU programming and the key frameworks and tools used 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 Plovdiv equips advanced developers with the skills to build, deploy, and tune custom AI operators. Participants will master CANN TIK and Apache TVM integration, enabling advanced optimization and scheduling on Huawei Ascend hardware for real-world performance.
This instructor-led, live training in Plovdiv (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 live training session in Plovdiv provides a comprehensive overview of CloudMatrix for scalable AI inference. Discover how to deploy, optimize, and monitor models using CANN and MindSpore. Practical exercises will guide you through packaging, conversion, serving, and performance tuning for both real-time and batch workloads.
This instructor-led, live training in Plovdiv (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 Plovdiv covers the core concepts and hands-on fundamentals of deploying AI models on Ascend edge devices using the CANN toolkit, helping participants build practical skills for compiling, optimizing, and managing constrained environments.
This instructor-led, live training in Plovdiv (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 Plovdiv (online or onsite) is aimed at beginner to intermediate 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, an 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 Plovdiv (online or onsite) targets 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.
This live training in Plovdiv introduces the CANN toolkit for AI framework developers. Learn to set up environments, convert models, and deploy applications on Ascend hardware using MindSpore, TensorFlow, or PyTorch, covering the full workflow from training to inference.
Optimize AI workloads on Ascend, Biren, and Cambricon with this hands-on training in Plovdiv. Learn to benchmark models, identify bottlenecks, and apply graph, kernel, and operator-level optimizations. Tune deployment pipelines to enhance throughput and latency across these leading platforms.
This instructor-led, live training in Plovdiv (online or on-site) targets graphic designers and animators at beginner to intermediate levels who wish to acquire skills in creating impressive animations, interactive media, and captivating web content using Adobe Animate.
By the conclusion of this training, participants will be capable of:
Navigating the Adobe Animate interface and its tools with confidence.
Creating and editing animations through the use of keyframes, motion tweens, and shape tweens.
Designing interactive animations and applications with ActionScript and JavaScript.
Incorporating audio and video elements into their projects.
Exporting animations for web, video, and mobile platforms.
Optimize neural network inference performance on Ascend AI processors with this advanced, instructor-led training in Plovdiv. Explore CANN's runtime architecture, leveraging the Graph Engine, TIK, and TVM for profiling, custom operator development, and memory bottleneck resolution.
Migrate CUDA applications to Chinese GPU architectures like Huawei Ascend and Biren in Plovdiv. This instructor-led course guides advanced programmers through code translation and performance optimization, covering hands-on labs for porting CUDA codebases to new SDKs.
This instructor-led, live training in Plovdiv (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, an 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 the CUDA API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
Use the 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 the 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 Plovdiv covers the fundamentals of Psdto3D101 for lenticular design. Participants will learn to create 3D, flip, morph, and motion effects, optimizing files for professional printing through interactive lectures and hands-on practical exercises.
This live training in Plovdiv assists intermediate AI developers in deploying models on Ascend processors through the CANN toolkit. You will learn to convert frameworks like PyTorch and TensorFlow, optimize performance, and troubleshoot issues to achieve efficient edge and cloud inference.
This live training in Plovdiv equips developers with the skills to program and optimize applications on Biren AI accelerators. Participants will learn the GPU architecture, set up the SDK, and translate CUDA code to Biren. It focuses on performance tuning and debugging techniques.
This instructor-led, live training in Plovdiv (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.
This instructor-led live training in Plovdiv equips developers with the skills to build and deploy AI models using BANGPy and Neuware on Cambricon MLUs. Participants will configure environments, develop optimized models, and integrate MLU acceleration into edge and data center applications.
This instructor-led, live training in Plovdiv (online or onsite) is designed for beginner-level system administrators and IT professionals who want to learn how 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 Plovdiv (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 Plovdiv (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 Plovdiv (online or onsite) is designed for C++ developers who want to use CUDA to accelerate applications, write high-performance GPU kernels, and leverage parallel algorithm libraries for scientific computing, data processing, and machine learning workloads.
This instructor-led, live training in Plovdiv (online or onsite) is aimed at C/C++ developers who wish to use CUDA to accelerate compute-intensive applications, including data processing, scientific simulations, machine learning workloads, and image processing pipelines.
This instructor-led live training in Plovdiv (offered online or onsite) is intended for software developers, data analysts, and technical experts who aim to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.
Join this hands-on training in Plovdiv to master FreeCAD, an open-source parametric 3D modeler. Learn to design real-world objects for construction or 3D printing, export to formats like STEP and STL, and automate workflows with Python. Perfect for designers and engineers.
This instructor-led, live training course in Plovdiv 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.
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Testimonials (2)
the point that Huba took the time to sit with me as the lesser knowledgeable of the application and go through each part and explain where i had gone wrong and how to correct the issue
Paul - Nottinghamshire Police
Course - Blender: 3D Modeling Fundamentals
Trainers energy and humor.
Tadeusz Kaluba - Nokia Solutions and Networks Sp. z o.o.
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