AI-Driven Drug Discovery and Development Training Course

This instructor-led, live training in Serbia (online or onsite) is designed for 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.

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

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

This instructor-led, live training in Serbia (online or onsite) is designed for biologists who wish to understand how AlphaFold works and utilize 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 four-day course provides an introduction to Artificial Intelligence and its practical applications. Upon completing the course, participants have the option to dedicate an additional day to working on a dedicated AI project.

This instructor-led, live training in Serbia (online or onsite) is aimed at researchers and developers who wish to use Chainer to build and train neural networks in Python while making the code easy to debug.

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

• Set up the necessary development environment to start developing neural network models.
• Define and implement neural network models using a comprehensible source code.
• Execute examples and modify existing algorithms to optimize deep learning training models while leveraging GPUs for high performance.

This instructor-led live training Serbia (available online or on-site) targets advanced professionals who aim to deepen their grasp of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

By the end 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 Serbia (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 Serbia, participants will learn to utilize Python libraries for NLP by building an application that processes images and generates captions.

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

• Design and code Deep Learning for NLP using Python libraries.
• Create Python code that processes a large volume of images and generates keywords.
• Produce Python code that generates captions from the identified keywords.

Audience

This course is designed for researchers and engineers in the field of Deep Learning who wish to leverage available tools, primarily open-source solutions, for the analysis of computer images.

Participants will engage with practical working examples.

This instructor-led, live course in Serbia (online or onsite) targets intermediate developers, data scientists, and AI professionals aiming to utilize TensorFlow Lite for Edge AI initiatives.

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

• Comprehend the foundational aspects of TensorFlow Lite and its role in Edge AI.
• Build and optimize AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on diverse edge devices.
• Employ tools and techniques for model conversion and optimization.
• Develop practical Edge AI applications using TensorFlow Lite.

This instructor-led, live training in Serbia (online or onsite) targets 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.
• Speed up computer vision applications using an FPGA.
• Run different CNN layers on the FPGA.
• Scale the application across multiple nodes in a Kubernetes cluster.

This instructor-led live training in Serbia (online or on-site) is designed for data scientists who want to use TensorFlow to analyze potential fraud data.

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

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

This instructor-led live training in Serbia (online or onsite) is targeted at developers and data scientists who wish to use Horovod for distributed deep learning and scale it across multiple GPUs in parallel.

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

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

This instructor-led live training in Serbia (online or onsite) is designed for technical professionals looking to apply deep learning models to image recognition applications.

Upon completion of this training, participants will be capable of:

• Installing and configuring Keras.
• Rapidly prototyping deep learning models.
• Implementing a convolutional network.
• Implementing a recurrent network.
• Running deep learning models on both CPU and GPU architectures.

This instructor-led, live training (online or onsite) is aimed at 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 how it works for 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 Serbia (online or onsite) 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.