Online Computer Graphics Training in Nigeria

Huawei Ascend comprises a range of AI processors engineered for superior performance in both inference and training tasks.

This live, instructor-led training session (available online or at your location) targets intermediate-level data scientists and AI engineers who aim to create and enhance neural network models utilizing Huawei’s Ascend platform alongside the CANN toolkit.

Upon completing this training, participants will be equipped to:

• Establish and configure the CANN development environment.
• Create AI applications leveraging MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs through tiling and custom operators.
• Deploy models across cloud or edge environments.

Course Format

• Interactive discussions and lectures.
• Practical application of the CANN toolkit and Huawei Ascend in sample projects.
• Guided exercises centred on model construction, training, and deployment.

Customization Options

• For tailored training aligned with your specific datasets or infrastructure, please get in touch with us to make arrangements.

Huawei’s AI stack—spanning from the low-level CANN SDK to the high-level MindSpore framework—delivers a tightly integrated environment for AI development and deployment, specifically optimised for Ascend hardware.

This instructor-led, live training (available online or onsite) is designed for beginner to intermediate technical professionals seeking to grasp how CANN and MindSpore components collaborate to support AI lifecycle management and infrastructure decisions.

Upon completing this training, participants will be able to:

• Understand the layered architecture of Huawei’s AI compute stack.
• Identify how CANN facilitates model optimisation and hardware-level deployment.
• Evaluate the MindSpore framework and toolchain in relation 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 focusing on the model flow from MindSpore to CANN.

Course Customisation Options

• For bespoke training requests, please contact us to arrange accordingly.

This instructor-led, live training in Nigeria (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.
• Use OpenACC API and libraries.
• Profile, debug, and optimize OpenACC programs.

The CANN SDK (Compute Architecture for Neural Networks) equips users with robust deployment and optimization tools for real-time AI applications in computer vision and natural language processing, particularly on Huawei Ascend hardware.

This instructor-led live training, available online or onsite, is designed for intermediate-level AI practitioners looking to build, deploy, and optimize vision and language models using the CANN SDK for production scenarios.

Upon completion of this training, participants will be able to:

• Deploy and optimize CV and NLP models using CANN and AscendCL.
• Utilize CANN utilities to convert models and integrate them into live pipelines.
• Optimize inference performance for tasks such as detection, classification, and sentiment analysis.
• Construct real-time CV/NLP pipelines tailored for edge or cloud-based deployment.

Course Format

• Interactive lectures accompanied by demonstrations.
• Hands-on labs featuring model deployment and performance profiling.
• Live pipeline design utilizing real-world CV and NLP use cases.

Customization Options

• To arrange customized training for this course, please get in touch with us.

This instructor-led, live training in Nigeria (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.

Leveraging CANN TIK (Tensor Instruction Kernel) alongside Apache TVM allows for sophisticated optimization and customization of AI model operators tailored to Huawei Ascend hardware.

This guided, live training session (available online or in-person) is designed for experienced system developers aiming to create, implement, and refine custom operators for AI models utilizing CANN’s TIK programming framework and TVM compiler integration.

Upon completing this training, participants will be equipped to:

• Craft and evaluate custom AI operators employing the TIK DSL for Ascend processors.
• Seamlessly embed custom operators into the CANN runtime and execution graphs.
• Utilize TVM for operator scheduling, automatic tuning, and performance benchmarking.
• Troubleshoot and enhance instruction-level performance for unique computational patterns.

Course Structure

• Engaging lectures paired with live demonstrations.
• Practical coding exercises involving operator development using TIK and TVM pipelines.
• Testing and tuning operations on Ascend hardware or simulated environments.

Customization Opportunities

• To arrange a tailored training session for this course, please reach out to us for arrangements.

This instructor-led, live training in Nigeria (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 Nigeria (online or onsite) is designed for artists, game developers, and complete beginners who wish to use Blender to create 3D models for interactive applications, video games, animated films, and other 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 robust AI inference on edge devices like the Ascend 310. It offers crucial tools for compiling, optimizing, and deploying models in environments where computing power and memory are limited.

This instructor-led, live training (available online or onsite) is designed for intermediate-level AI developers and integrators who aim 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 with MindSpore Lite and AscendCL.
• Enhance model performance within constrained compute and memory settings.
• Deploy and monitor AI applications in real-world edge scenarios.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on lab exercises 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 get in touch to arrange it.

This instructor-led, live training in Nigeria (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 Nigeria (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 Nigeria (online or onsite) is designed for artists, game developers, or absolute beginners who want 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:

• Grasp the principles and core concepts of 3D modeling.
• Explore a variety of modes and tools for modeling and editing 3D meshes.
• Utilize tools for UV mapping/unwrapping, sculpting, and painting 3D models during rendering.

CANN (Compute Architecture for Neural Networks) is Huawei’s toolkit for AI computing, designed to compile, optimise, and deploy AI models on Ascend AI processors.

This instructor-led, live training (available online or onsite) is tailored for beginner-level AI developers who want to grasp how CANN fits into the model lifecycle—from training to deployment—and how it integrates 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.
• Establish a development environment featuring CANN and MindSpore.
• Convert and deploy a basic AI model onto Ascend hardware.
• Acquire foundational knowledge to support future CANN optimization or integration initiatives.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs focused on simple model deployment.
• Step-by-step walkthroughs of the CANN toolchain and integration points.

Course Customization Options

• To arrange customized training for this course, please contact us to make the necessary arrangements.

Ascend, Biren, and Cambricon stand as premier AI hardware platforms in China, providing distinct acceleration and profiling capabilities designed for large-scale AI production workloads.

This instructor-led live training, available both online and onsite, targets advanced AI infrastructure and performance engineers seeking to optimise model inference and training workflows across diverse Chinese AI chip ecosystems.

Upon completing this training, participants will be equipped to:

• Conduct benchmarking of models on Ascend, Biren, and Cambricon platforms.
• Pinpoint system bottlenecks and identify inefficiencies in memory and compute usage.
• Implement optimisations at the graph, kernel, and operator levels.
• Refine deployment pipelines to enhance throughput and reduce latency.

Course Format

• Interactive lectures coupled with group discussions.
• Practical application of profiling and optimisation tools on each specific platform.
• Guided exercises centred on real-world tuning scenarios.

Customisation Options

• To arrange customised training tailored to your specific performance environment or model architecture, please reach out to us for arrangement.

This instructor-led, live training in Nigeria (online or onsite) is designed for beginner to intermediate graphic designers and animators who aim 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.

The CANN SDK (Compute Architecture for Neural Networks) serves as Huawei’s foundational AI compute platform, enabling developers to fine-tune and maximize the performance of neural networks deployed on Ascend AI processors.

This instructor-led live training, available both online and onsite, targets advanced AI developers and system engineers looking 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 equipped to:

• Grasp CANN's runtime architecture and its performance lifecycle.
• Utilize profiling tools and the Graph Engine for detailed performance analysis and optimization.
• Develop and optimize custom operators using TIK and TVM.
• Address memory bottlenecks and boost model throughput.

Course Format

• Interactive lectures and discussions.
• Practical hands-on labs featuring real-time profiling and operator tuning.
• Optimization exercises centered on edge-case deployment scenarios.

Customization Options

• To request a tailored training program for this course, please reach out to us to make arrangements.

Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide CUDA alternatives specifically designed for the local AI and HPC markets.

This instructor-led live training, available online or onsite, targets advanced-level GPU programmers and infrastructure specialists looking 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 Camricon BANGPy environments.
• Compare performance metrics and identify optimization opportunities across platforms.
• Tackle practical challenges related to cross-architecture support and deployment.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for code translation and performance comparison.
• Guided exercises focusing on multi-GPU adaptation strategies.

Course Customization Options

• To arrange customized training for this course tailored to your platform or CUDA project, please contact us.

This instructor-led, live training in Nigeria (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.

97% de clients satisfaits.

Psdto3D101 is a specialised 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 optimise 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 customised training for this course, please contact us to arrange.

CANN (Compute Architecture for Neural Networks) serves as Huawei’s AI compute stack, designed to deploy and optimise AI models on Ascend AI processors.

This instructor-led, live training, available both online and onsite, targets intermediate-level AI developers and engineers who aim to efficiently deploy trained AI models onto Huawei Ascend hardware using the CANN toolkit alongside tools like MindSpore, TensorFlow, or PyTorch.

By the conclusion of this training, participants will be able to:

• Grasp the CANN architecture and its significance within the AI deployment pipeline.
• Convert and adapt models from popular frameworks into formats compatible with Ascend.
• Utilise tools such as ATC, OM model conversion, and MindSpore for inference on edge and cloud environments.
• Identify deployment issues and optimise performance on Ascend hardware.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on lab sessions using CANN tools and Ascend simulators or devices.
• Practical deployment scenarios based on real-world AI models.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Biren AI Accelerators are high-performance GPUs engineered for AI and HPC workloads, offering robust support for large-scale training and inference.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced developers who want 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 Nigeria (online or onsite) is designed for artists, game developers, and absolute beginners who want 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 various modes and tools for modelling 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 to optimize inference and training for both edge devices and data center environments.

This instructor-led live training, available either online or onsite, targets intermediate developers who want to build and deploy AI models utilizing the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be able to:

• Set up and configure the development environments for BANGPy and Neuware.
• Develop and optimize Python- and C++-based models tailored for Cambricon MLUs.
• Deploy models to edge and data center devices operating on the Neuware runtime.
• Integrate machine learning workflows with acceleration features specific to MLU.

Course Format

• Interactive lectures and discussions.
• Practical, hands-on development and deployment using BANGPy and Neuware.
• Guided exercises emphasizing optimization, integration, and testing.

Customization Options

• To request a tailored training session based on your specific Cambricon device model or use case, please contact us to arrange.

This instructor-led, live training in Nigeria (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.

Upon completing this training, participants will be able to:

• Grasp the architecture, components, and capabilities of CUDA.
• Install and set up CUDA environments.
• Manage and optimize CUDA resources effectively.
• Debug and resolve common CUDA issues.

This instructor-led live training in Nigeria (online or onsite) targets beginner to intermediate 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 Nigeria (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 Nigeria (online or onsite) is aimed at C++ developers who wish 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 Nigeria (online or onsite) targets 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 Nigeria (online or onsite) is aimed at software developers, data analysts, and technical professionals who wish to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.

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 course in Nigeria 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.