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. Onsite live Computer Graphics trainings in Belo Horizonte can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Belo Horizonte - Amadeus Business Tower
6594 Contorno Avenue, floors 16 and 17, Belo Horizonte, Brazil
The Belo Horizonte Amadeus Business Tower Center occupies the 16th and 17th floors of a modern high-rise on one of the city's main streets, located in the prestigious Stavassi commercial district. The building features intelligent hi-tech systems, a cyber café, heliport and parking. It is 25 minutes from Pampulha Airport for domestic flights.
Huawei Ascend comprises a series of AI processors engineered for superior inference and training performance.
This instructor-led training session, available both online and onsite, targets intermediate AI engineers and data scientists aiming to create and refine neural network models utilizing Huawei’s Ascend platform alongside the CANN toolkit.
Upon completion of this program, participants will gain the ability to:
Establish and configure the CANN development environment.
Construct AI applications through MindSpore and CloudMatrix workflows.
Enhance performance on Ascend NPUs via custom operators and tiling techniques.
Deploy models to either edge or cloud settings.
Course Format
Engaging lectures and discussions.
Practical application of Huawei Ascend and the CANN toolkit within sample projects.
Supervised exercises concentrating on model creation, training, and deployment.
Options for Course Customization
For tailored training needs aligned with your specific infrastructure or datasets, please reach out to us to arrange.
Huawei’s AI stack, spanning from the low-level CANN SDK to the high-level MindSpore framework, provides a tightly integrated environment for AI development and deployment, specifically optimized for Ascend hardware.
This live, instructor-led training (available online or onsite) targets beginner to intermediate technical professionals who want to understand how CANN and MindSpore components collaborate to support AI lifecycle management and infrastructure decisions.
Upon completion of this training, participants will be able to:
Comprehend the layered architecture of Huawei’s AI compute stack.
Recognize how CANN facilitates model optimization and hardware-level deployment.
Assess the MindSpore framework and its toolchain in comparison to industry alternatives.
Position Huawei's AI stack within enterprise or cloud/on-premises environments.
Course Format
Interactive lectures and discussions.
Live system demonstrations and case-based walkthroughs.
Optional guided labs covering the model flow from MindSpore to CANN.
Course Customization Options
To request customized training for this course, please contact us to arrange.
This instructor-led, live training in Belo Horizonte (online or onsite) is aimed at beginner 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.
The CANN SDK (Compute Architecture for Neural Networks) offers robust deployment and optimization tools tailored for real-time AI applications in computer vision and NLP, particularly on Huawei Ascend hardware.
This instructor-led live training (available online or onsite) targets intermediate-level AI practitioners looking to build, deploy, and optimize vision and language models with the CANN SDK for production environments.
Upon completion of this training, participants will be able to:
Deploy and optimize CV and NLP models utilizing CANN and AscendCL.
Leverage CANN tools to convert models and integrate them into live pipelines.
Enhance inference performance for tasks such as detection, classification, and sentiment analysis.
Construct real-time CV/NLP pipelines for edge or cloud-based deployment scenarios.
Course Format
Interactive lectures combined with live demonstrations.
Practical labs focused on model deployment and performance profiling.
Real-time pipeline design using practical CV and NLP use cases.
Course Customization Options
To request a customized training session for this course, please reach out to us for arrangement.
This instructor-led, live training in Belo Horizonte (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.
The combination of CANN TIK (Tensor Instruction Kernel) and Apache TVM facilitates advanced optimization and customization of AI model operators specifically for Huawei Ascend hardware.
This instructor-led training session, available both online and in-person, targets advanced system developers looking to construct, deploy, and fine-tune custom operators for AI models utilizing CANN’s TIK programming model and its integration with the TVM compiler.
Upon completing this training, participants will be equipped to:
Develop and test custom AI operators by leveraging the TIK DSL for Ascend processors.
Incorporate custom operators into the CANN runtime and execution graph.
Apply TVM for operator scheduling, automatic tuning, and performance benchmarking.
Debug and enhance instruction-level performance for complex custom computation patterns.
Course Format
Interactive lectures combined with live demonstrations.
Practical coding exercises for operators using TIK and TVM pipelines.
Hands-on testing and tuning on Ascend hardware or in simulator environments.
Options for Course Customization
To request a tailored version of this course, please get in touch with us to arrange the details.
This instructor-led, live training in Belo Horizonte (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 platform for AI development and deployment, designed to support scalable, production-grade inference pipelines.
This instructor-led live training (available online or onsite) targets beginner to intermediate AI professionals looking to deploy and monitor AI models using the CloudMatrix platform, integrated with CANN and MindSpore.
Upon completion of this training, participants will be able to:
Utilize CloudMatrix for model packaging, deployment, and serving.
Convert and optimize models for Ascend chipsets.
Establish pipelines for both real-time and batch inference tasks.
Monitor deployments and tune performance in production environments.
Course Format
Interactive lectures and discussions.
Hands-on practice with CloudMatrix in real deployment scenarios.
Guided exercises focusing on conversion, optimization, and scaling.
Customization Options
To request a customized version of this course tailored to your specific AI infrastructure or cloud environment, please contact us to make arrangements.
This instructor-led live training, held in Belo Horizonte (online or onsite), is tailored for artists, game developers, or complete beginners who want to use Blender to craft 3D models for interactive applications, video games, animated films, and similar projects.
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.
Huawei's Ascend CANN toolkit empowers AI inference on edge devices like the Ascend 310. It offers critical tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.
This instructor-led, live training (available online or onsite) targets intermediate-level AI developers and integrators who want to deploy and optimize models on Ascend edge devices using the CANN toolchain.
Upon completing this training, participants will be able to:
Prepare and convert AI models for the Ascend 310 using CANN tools.
Construct lightweight inference pipelines using MindSpore Lite and AscendCL.
Optimize model performance for scenarios with constrained compute and memory.
Deploy and monitor AI applications in real-world edge use cases.
Format of the Course
Interactive lectures and demonstrations.
Hands-on labs featuring edge-specific models and scenarios.
Live deployment examples on virtual or physical edge hardware.
Course Customization Options
To request customized training for this course, please contact us to arrange it.
This instructor-led live training in Belo Horizonte (online or onsite) targets beginner to intermediate 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, an 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 Belo Horizonte (online or onsite) is intended for beginner 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, 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 Belo Horizonte (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 rendering.
CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing toolkit designed to compile, optimize, and deploy AI models on Ascend AI processors.
This instructor-led live training, available both online and onsite, is tailored for beginner-level AI developers who want to grasp how CANN integrates into the model lifecycle, from training through deployment, and how it collaborates with frameworks such as MindSpore, TensorFlow, and PyTorch.
Upon completing this training, participants will be able to:
Comprehend the purpose and architecture of the CANN toolkit.
Configure a development environment featuring CANN and MindSpore.
Convert and deploy a simple AI model onto Ascend hardware.
Acquire foundational knowledge to support future CANN optimization or integration initiatives.
Course Format
Interactive lectures and discussions.
Practical labs focused on simple model deployment.
Step-by-step walkthroughs of the CANN toolchain and its integration points.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Ascend, Biren, and Cambricon represent the forefront of AI hardware platforms in China, each providing distinct acceleration and profiling capabilities tailored for large-scale AI workloads.
This instructor-led live training, available both online and onsite, is designed for advanced AI infrastructure and performance engineers seeking to optimize model inference and training workflows across these diverse Chinese AI chip ecosystems.
Upon completion of this training, participants will be equipped to:
Conduct benchmarking of models on Ascend, Biren, and Cambricon platforms.
Diagnose system bottlenecks and identify memory or compute inefficiencies.
Implement optimizations at the graph, kernel, and operator levels.
Refine deployment pipelines to enhance throughput and reduce latency.
Course Format
Interactive lectures and discussions.
Practical application of profiling and optimization tools on each platform.
Guided exercises centered on real-world tuning scenarios.
Customization Options
To arrange customized training tailored to your specific performance environment or model architecture, please contact us.
This instructor-led, live training in Belo Horizonte (online or in-person) targets beginner to intermediate graphic designers and animators who wish to learn how to craft 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 master its tools.
Construct and modify animations utilizing keyframes, motion tweens, and shape tweens.
Develop interactive animations and applications using ActionScript and JavaScript.
Integrate audio and video components into their projects.
Export animations for web, video, and mobile platforms.
The CANN SDK (Compute Architecture for Neural Networks) serves as Huawei’s foundational AI compute platform, enabling developers to refine and boost the performance of neural networks deployed on Ascend AI processors.
This instructor-led live training, available either online or on-site, is designed for advanced AI developers and system engineers aiming to enhance inference performance through CANN’s sophisticated toolset, which includes the Graph Engine, TIK, and custom operator development capabilities.
Upon completing this training, participants will be able to:
Grasp CANN’s runtime architecture and its performance lifecycle.
Utilize profiling tools and the Graph Engine for performance analysis and optimization.
Develop and optimize custom operators using TIK and TVM.
Address memory bottlenecks and increase model throughput.
Course Format
Interactive lectures and discussions.
Practical labs featuring real-time profiling and operator tuning.
Optimization exercises based on edge-case deployment scenarios.
Customization Options
To arrange a tailored version of this course, please contact us.
Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide CUDA alternatives specifically designed for the local AI and high-performance computing (HPC) markets.
This instructor-led live training (available online or onsite) is designed for advanced GPU programmers and infrastructure specialists seeking to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.
Upon completion of this training, participants will be able to:
Assess the compatibility of current CUDA workloads with Chinese chip alternatives.
Port CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
Compare performance metrics and identify optimization opportunities across different platforms.
Address practical challenges related to cross-architecture support and deployment.
Course Format
Interactive lectures and discussions.
Practical labs focused on code translation and performance comparisons.
Guided exercises centered on multi-GPU adaptation strategies.
Customization Options
To request a customized training for this course tailored to your specific platform or CUDA project, please contact us to arrange.
This instructor-led, live training in Belo Horizonte (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.
Psdto3D101 is a specialized software tool designed for creating lenticular files with 3D effects, flip, morph, and motion designs. This course provides participants with the knowledge and practical skills to manage and apply Psdto3D101 for producing professional lenticular outputs, covering both management and creative aspects of the software.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level graphic and print professionals who wish to create, manage, and optimize lenticular files using Psdto3D101 software.
By the end of this training, participants will be able to:
Understand the fundamentals of lenticular printing and design.
Navigate and configure Psdto3D101 for different project types.
Create 3D, flip, and motion effects using layers and sequences.
Export and prepare lenticular files for professional printing.
Format of the Course
Interactive lecture and discussion.
Practical exercises using Psdto3D101 software.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
CANN (Compute Architecture for Neural Networks) serves as Huawei’s AI compute stack, designed for deploying and optimizing AI models on Ascend AI processors.
This instructor-led training session, available both online and onsite, is tailored for intermediate-level AI developers and engineers aiming to efficiently deploy trained AI models onto Huawei Ascend hardware. The curriculum utilizes the CANN toolkit alongside frameworks such as MindSpore, TensorFlow, and PyTorch.
Upon completion of this training, participants will be equipped to:
Comprehend the CANN architecture and its significance within the AI deployment pipeline.
Convert and adapt models from leading frameworks into formats compatible with Ascend.
Leverage tools like ATC, OM model conversion, and MindSpore for inference tasks in both edge and cloud environments.
Identify deployment challenges and optimize performance on Ascend hardware.
Course Format
Interactive lectures paired with live demonstrations.
Practical lab exercises utilizing CANN tools and Ascend simulators or physical devices.
Real-world deployment scenarios based on actual AI models.
Customization Options
To arrange a customized training version of this course, please get in touch with us.
Biren AI Accelerators are high-performance GPUs engineered for AI and HPC workloads, supporting large-scale training and inference.
This instructor-led live training (available online or onsite) targets intermediate to advanced 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 Belo Horizonte (online or in-person) 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, and more.
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 designed for optimized inference and training in both edge computing and data center environments.
This instructor-led, live training session (available online or on-site) is designed for intermediate-level developers who want to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.
Upon completing this training, participants will be able to:
Set up and configure development environments for BANGPy and Neuware.
Develop and optimize Python- and C++-based models tailored for Cambricon MLUs.
Deploy models to edge devices and data centers running the Neuware runtime.
Integrate machine learning workflows with acceleration features specific to MLUs.
Course Format
Interactive lectures and discussions.
Hands-on practice using BANGPy and Neuware for development and deployment.
Guided exercises focusing on optimization, integration, and testing.
Course Customization Options
To request a customized training session tailored to your specific Cambricon device model or use case, please contact us to arrange.
This instructor-led, live training in Belo Horizonte (online or onsite) is designed for beginner-level system administrators and IT professionals who want 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 Belo Horizonte (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 Belo Horizonte (available online or onsite) is aimed at designers, mechanical engineers, and anyone who wants 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 Belo Horizonte (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 course is ideal for anyone eager to begin their graphic design journey with Affinity Designer, a highly popular and versatile vector graphics application. Whether you are new to computer graphics or seeking a robust foundation, this course will guide you step-by-step to master the essential features and tools required for creating professional designs.
Throughout the course:
You will learn to navigate the Affinity Designer interface, enabling you to utilize its features efficiently.
You will gain proficiency in the fundamental tools for drawing and editing shapes, empowering you to develop your own illustrations and graphics.
You will understand how to effectively manage layers and incorporate colors and text into your designs.
You will master the essentials of exporting your designs in various formats, preparing them for either print or online publication.
Upon completion, you will be capable of producing simple graphics, logos, posters, and other visual materials using Affinity Designer. This course provides a solid foundation that will support your further development of graphic design skills.
This instructor-led live training (available online or onsite) is designed for beginner to intermediate developers looking to build mobile AR applications using ARToolKit. The course covers its latest mobile capabilities, including natural feature tracking, calibration techniques, and integration with external sensors.
This instructor-led live training in Belo Horizonte (available online or onsite) targets web designers looking to utilize Maya for creating 3D animations.
By the conclusion of this training, participants will be capable of:
Creating realistic models and textures in Maya.
Animating and rendering projects for high-quality playback.
This instructor-led, live training course in Belo Horizonte 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 Belo Horizonte (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 begin building 3D graphics and workflows.
Understand basic USD composition and apply modifications to enhance 3D assets and scenes.
Share, combine, and transform multiple assets using supported USD plugins for third-party applications (Maya, Katana, and Houdini).
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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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