Matlab for Deep Learning Training Course

This instructor-led, live training in the UAE (online or onsite) targets intermediate to advanced data scientists, machine learning engineers, deep learning researchers, and computer vision experts seeking to expand their knowledge and skills in deep learning for text-to-image generation.

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

• Understand advanced deep learning architectures and techniques for text-to-image generation.
• Implement complex models and optimizations for high-quality image synthesis.
• Optimize performance and scalability for large datasets and complex models.
• Tune hyperparameters for better model performance and generalization.
• Integrate Stable Diffusion with other deep learning frameworks and tools.

This instructor-led, live training in the UAE (online or onsite) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies.

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

• Understand the basic principles of AlphaFold.
• Learn how AlphaFold works.
• Learn how to interpret AlphaFold predictions and results.

This intensive four-day program introduces the fundamentals of artificial intelligence and its practical applications. Upon completion, participants have the option to extend their learning by dedicating an additional day to executing a hands-on AI project.

This instructor-led live training in the UAE (available online or onsite) is designed for researchers and developers who wish to use Chainer to build and train neural networks in Python, while ensuring the code is easy to debug.

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

• Set up the required development environment to start building neural network models.
• Define and implement neural network models using clear source code.
• Execute examples and modify existing algorithms to optimize deep learning training models, leveraging GPUs for high performance.

This instructor-led live training in the UAE (online or onsite) is designed for advanced professionals aiming to deepen their grasp of computer vision and explore TensorFlow’s capabilities for building advanced vision models using Google Colab.

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

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualize and interpret the results of image classification models.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.

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

• Set up and navigate Google Colab for deep learning projects.
• Understand the fundamentals of neural networks.
• Implement deep learning models using TensorFlow.
• Train and evaluate deep learning models.
• Utilize advanced features of TensorFlow for deep learning.

In this instructor-led, live training in the UAE, participants will learn to use Python libraries for NLP as they create an application that processes a set of pictures and generates captions.

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

• Design and code DL for NLP using Python libraries.
• Create Python code that reads a substantially huge collection of pictures and generates keywords.
• Create Python Code that generates captions from the detected keywords.

Target Audience

Designed for researchers and engineers in Deep Learning who wish to leverage accessible tools (primarily open-source solutions) to analyze digital imagery.

The course includes practical, hands-on examples.

This instructor-led live training offered in the UAE (online or onsite) caters to intermediate-level developers, data scientists, and AI practitioners aiming to harness TensorFlow Lite for Edge AI applications.

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

• Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
• Develop and optimize AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on various edge devices.
• Utilize tools and techniques for model conversion and optimization.
• Implement practical Edge AI applications using TensorFlow Lite.

This instructor-led, live training in the UAE (online or onsite) is aimed at data scientists who wish to accelerate real-time machine learning applications and deploy them at scale.

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

• Install the OpenVINO toolkit.
• Accelerate a computer vision application using an FPGA.
• Execute different CNN layers on the FPGA.
• Scale the application across multiple nodes in a Kubernetes cluster.

This instructor-led live training in the UAE (online or onsite) is tailored for data scientists aiming to apply TensorFlow to the analysis of potential fraud data.

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

• Construct a fraud detection model using Python and TensorFlow.
• Build linear regression models to predict fraud.
• Develop an end-to-end AI application for analyzing fraud data.

This instructor-led live training in the UAE (online or onsite) is designed for developers and data scientists who want to utilize Horovod for distributed deep learning training and scale it across multiple GPUs in parallel.

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

• Set up the required development environment to begin running deep learning trainings.
• Install and configure Horovod to train models using TensorFlow, Keras, PyTorch, and Apache MXNet.
• Scale deep learning training with Horovod to run on multiple GPUs.

This instructor-led live training in the UAE (online or onsite) is designed for technical professionals interested in applying deep learning models to image recognition tasks.

By the end of the course, participants will be able to:

• Install and configure Keras.
• Quickly prototype deep learning models.
• Implement a convolutional network.
• Implement a recurrent network.
• Execute a deep learning model on both a CPU and GPU.

This instructor-led live training (available online or onsite) is designed for data scientists, machine learning engineers, and computer vision researchers who wish to leverage Stable Diffusion to generate high-quality images for a variety of use cases.

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

• Understand the principles of Stable Diffusion and its workings in image generation.
• Build and train Stable Diffusion models for image generation tasks.
• Apply Stable Diffusion to various image generation scenarios, such as inpainting, outpainting, and image-to-image translation.
• Optimize the performance and stability of Stable Diffusion models.

This instructor-led, live training in the UAE (online or on-site) targets engineers who wish to write, load, and run machine learning models on very small embedded devices.

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

• Install TensorFlow Lite.
• Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
• Add AI to hardware devices without relying on network connectivity.