Delivered either online or on-site, our instructor-led Deep Learning (DL) training programs utilize hands-on exercises to illustrate the core principles and practical uses of Deep Learning. These courses explore key areas including deep machine learning, deep structured learning, and hierarchical learning.
Deep Learning training can be accessed as "online live training" or "onsite live training". The online option, also referred to as "remote live training", is facilitated through an interactive remote desktop. Alternatively, onsite live training can be conducted at your premises in Porto Alegre or within NobleProg's corporate training centers located in Porto Alegre.
NobleProg -- Your Local Training Provider
Porto Alegre - Platinum Building
Carlos Gomes Avenue, 700, Porto Alegre, Brazil, 90480-000
Platinum Building has many amenities close by. The Boa Vista district is a major corporate center in this sophisticated and progressive port city. Also the business center is six kilometers from the international airport and well served by public transport.
Porto Alegre - Guaiba Business Center
Av. Dolorez Alcaraz Caldas, 90 Porto Alegre RS, Praia de Belas, Brasil, 90110-180
Be at the centre of a lively business district in Praia De Belas, surrounded by courthouses and government offices. Centro Empresarial Guaiba is a distinctive Class A building in the thriving state capital of Porto Alegre.
This instructor-led live training in Porto Alegre (online or onsite) targets intermediate developers, data scientists, and AI practitioners who aim to utilize 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 Porto Alegre (online or onsite) targets advanced professionals seeking 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 instructor-led, live training in Porto Alegre (online or on-site) targets 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.
This instructor-led, live training in Porto Alegre (online or in-person) targets advanced-level professionals aiming to specialize in state-of-the-art deep learning techniques for NLU.
Upon completion of this training, participants will be capable of:
Grasping the fundamental distinctions between NLU and NLP models.
Implementing advanced deep learning techniques for NLU applications.
Exploring deep architectures, including transformers and attention mechanisms.
Leveraging emerging NLU trends to develop sophisticated AI systems.
This instructor-led, live training in Porto Alegre (online or onsite) is intended for advanced professionals seeking to explore state-of-the-art XAI techniques for deep learning models, focusing on the development of interpretable AI systems.
By the end of this training, participants will be able to:
Understand the challenges of explainability in deep learning.
Implement advanced XAI techniques for neural networks.
Interpret decisions made by deep learning models.
Evaluate the trade-offs between performance and transparency.
This instructor-led, live training in Porto Alegre (online or on-site) is designed for intermediate to advanced data scientists, machine learning engineers, deep learning researchers, and computer vision experts who want to deepen 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 to enhance model performance and generalization.
Integrate Stable Diffusion with other deep learning frameworks and tools.
This instructor-led, live training in Porto Alegre (online or onsite) is aimed at advanced-level professionals who wish to leverage AI techniques to revolutionize drug discovery and development processes.
By the end of this training, participants will be able to:
Understand the role of AI in drug discovery and development.
Apply machine learning techniques to predict molecular properties and interactions.
Use deep learning models for virtual screening and lead optimization.
Integrate AI-driven approaches into the clinical trial process.
This instructor-led live training in Porto Alegre (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 instructor-led, live training in Porto Alegre (online or onsite) is designed for beginner to intermediate-level developers who wish to leverage Large Language Models for a variety of natural language tasks.
Upon completion of this training, participants will be able to:
Configure a development environment that incorporates a popular LLM.
Construct a basic LLM and fine-tune it using a custom dataset.
Apply LLMs to diverse natural language tasks such as text summarization, question answering, and text generation.
Debug and evaluate LLMs utilizing tools like TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
This instructor-led, live training (available online or onsite) targets 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 image generation process.
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.
In this instructor-led, live training in Porto Alegre, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data.
By the end of this training, participants will be able to:
Implement machine learning algorithms and techniques for solving complex problems.
Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
Push Python algorithms to their maximum potential.
Use libraries and packages such as NumPy and Theano.
This hands-on training in Porto Alegre enables programmers to construct AI models from the ground up using Python. Participants will gain expertise in supervised learning, neural networks, and unsupervised techniques by leveraging scikit-learn and Apache Spark. The curriculum emphasizes practical Jupyter exercises aimed at solving real-world problems.
This instructor-led training on Porto Alegre delves into the theoretical foundations and practical implementation of Deep Reinforcement Learning using Python. Participants will learn to construct and train DRL agents with TensorFlow or PyTorch, leveraging key algorithms like DQN and PPO to address complex, real-world challenges.
A foundational course on Porto Alegre that delves into the basics of AI, ranging from intelligent agents to machine learning. It empowers executives and architects to evaluate new AI trends, implement practical solutions, and boost business agility through strategic automation.
Explore how Machine Learning and Deep Learning are reshaping the automotive sector. This Porto Alegre course delves into core concepts, spanning from simple automation to autonomous decision-making, while covering neural networks and providing practical TensorFlow examples for real-world implementation.
This three-day program in Porto Alegre delves into both the theoretical underpinnings and practical applications of Artificial Neural Networks, Machine Learning, and Deep Learning. Participants will examine various network architectures, learning mechanisms, and mathematical bases, progressing from foundational concepts like basic perceptrons to sophisticated deep learning methodologies.
This instructor-led, live training in Porto Alegre (online or onsite) offers an introduction to the fields of pattern recognition and machine learning. It covers practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.
Upon completion of this training, participants will be able to:
Apply fundamental statistical methods to pattern recognition.
Utilize essential models, such as neural networks and kernel methods, for data analysis.
Implement advanced techniques to solve complex problems.
Enhance prediction accuracy by integrating various models.
This instructor-led live training in Porto Alegre (online or on-site) is designed for 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.
This instructor-led live training in Porto Alegre (online or onsite) targets data scientists who wish 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.
In this instructor-led live training, participants will learn how to use MATLAB to design, build, and visualize a convolutional neural network for image recognition.
By the end of this training, participants will be able to:
Build a deep learning model
Automate data labeling
Work with models from Caffe and TensorFlow-Keras
Train data using multiple GPUs, the cloud, or clusters
Audience
Developers
Engineers
Domain experts
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training in Porto Alegre (online or onsite) is aimed at developers and data scientists who wish to use Tensorflow 2.x to build predictors, classifiers, generative models, neural networks and so on.
By the end of this training, participants will be able to:
Install and configure TensorFlow 2.x.
Understand the benefits of TensorFlow 2.x over previous versions.
Build deep learning models.
Implement an advanced image classifier.
Deploy a deep learning model to the cloud, mobile and IoT devices.
This comprehensive 35-hour course on Porto Alegre delves into the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Learners will gain practical, hands-on experience with Theano and TensorFlow, acquiring the skills necessary to build, train, and deploy production-ready deep learning models for real-world scenarios.
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Testimonials (5)
Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.
Matthew Gay - Tarsus Pharmaceuticals
Course - Artificial Intelligence (AI) Overview
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
Magdalena - Samsung Electronics Polska Sp. z o.o.
Course - Deep Learning with TensorFlow 2
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
That it was applying real company data.
Trainer had a very good approach by making trainees participate and compete
Jimena Esquivel - Zaklad Uslugowy Hakoman Andrzej Cybulski
Course - Applied AI from Scratch in Python
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
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