Python and Deep Learning with OpenCV 4 Training Course

This instructor-led, live training in Norway (online or onsite) is designed for intermediate to advanced data scientists, machine learning engineers, deep learning researchers, and computer vision experts who wish 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:

• Comprehend advanced deep learning architectures and methodologies for text-to-image generation.
• Deploy complex models and optimization strategies to achieve high-fidelity image synthesis.
• Enhance performance and scalability when working with large datasets and intricate models.
• Refine hyperparameters to improve model performance and generalization capabilities.
• Seamlessly integrate Stable Diffusion with other deep learning frameworks and tools.

This instructor-led, live training in Norway (online or onsite) targets 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.

Spanning four days, this course provides a foundational introduction to artificial intelligence and its practical applications. Participants may also choose to extend their learning by dedicating an additional day to working on a real-world AI project upon completing the course.

This instructor-led live training in Norway (online or onsite) is aimed at 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 necessary development environment to start developing neural network models.
• Define and implement neural network models using 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 in Norway (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding 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 live, instructor-led training in Norway (online or onsite) targets intermediate-level data scientists and developers eager to understand and apply deep learning techniques within the Google Colab ecosystem.

By the conclusion 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 Norway, 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.

Audience

This course is designed for deep learning researchers and engineers who wish to leverage available tools (primarily open-source) to analyze computer images.

The course includes practical working examples.

This live, instructor-led training, conducted in Norway (either online or onsite), is designed for intermediate-level developers, data scientists, and AI professionals seeking to apply TensorFlow Lite for Edge AI solutions.

By the conclusion of this training, participants will be capable of:

• Comprehending the basics of TensorFlow Lite and its function in Edge AI.
• Developing and optimizing AI models via TensorFlow Lite.
• Deploying TensorFlow Lite models onto various edge devices.
• Applying tools and methods for model conversion and optimization.
• Implementing functional Edge AI applications using TensorFlow Lite.

This instructor-led, live training in Norway (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.
• 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 Norway (online or on-site) targets data scientists who intend 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 Norway (online or onsite) is aimed at developers or data scientists who wish to use Horovod to run distributed deep learning trainings and scale it up to run across multiple GPUs in parallel.

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

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

This instructor-led, live training in Norway (online or onsite) is aimed at technical persons who wish to apply deep learning model to image recognition applications.

By the end of this training, 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 looking to leverage Stable Diffusion for generating high-quality images across various use cases.

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

• Understand the principles of Stable Diffusion and its operational logic 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 Norway (online or onsite) is aimed at 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.