Online or onsite, instructor-led live Neural Network training courses demonstrate through interactive discussion and hands-on practice how to construct Neural Networks using a number of mostly open-source toolkits and libraries as well as how to utilize the power of advanced hardware (GPUs) and optimization techniques involving distributed computing and big data. Our Neural Network courses are based on popular programming languages such as Python, Java, R language, and powerful libraries, including TensorFlow, Torch, Caffe, Theano and more. Our Neural Network courses cover both theory and implementation using a number of neural network implementations such as Deep Neural Networks (DNN), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN).
Neural Network training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Neural Networks trainings in Quito can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Quito - Av Eloy Alfaro
5915 Ave, Av Eloy Alfaro E6-24 y, Quito, ecuador, 170102
Give your latest ideas a boost in Batán Alto with the flexible workspaces at 5915 Av Eloy Alfaro. Enjoy inspiring views over an eclectic cityscape, set against the spectacular backdrop of Quito's Andean foothills.
This instructor-led, live training in Quito (online or onsite) is aimed at advanced-level professionals who wish to explore state-of-the-art XAI techniques for deep learning models, with a focus on building 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 practical training in Quito helps programmers build AI models from scratch using Python. You will master supervised learning, neural networks, and unsupervised techniques using scikit-learn and Apache Spark. It focuses on hands-on Jupyter exercises for real-world problem solving.
This instructor-led training in Quito covers the theoretical foundations and practical implementation of Deep Reinforcement Learning using Python. Participants will build and train DRL agents with TensorFlow or PyTorch, applying key algorithms like DQN and PPO to solve complex real-world problems.
An introductory training in Quito exploring AI fundamentals, from intelligent agents to machine learning. It equips executives and architects to assess emerging AI trends, integrate practical solutions, and accelerate business agility through automated strategies.
Explore how Machine Learning and Deep Learning transform the automotive sector. This Quito course covers core concepts from simple automation to autonomous decision-making, including neural networks and practical TensorFlow examples for real-world applications.
This three-day program in Quito covers the theory and practice of Artificial Neural Networks, Machine Learning, and Deep Learning. Participants will explore network architectures, learning mechanisms, and mathematical foundations, moving from basic perceptrons to advanced deep learning techniques.
This instructor-led, live training in Quito (online or onsite) provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.
By the end of this training, participants will be able to:
Apply core statistical methods to pattern recognition.
Use key models like neural networks and kernel methods for data analysis.
Implement advanced techniques for complex problem-solving.
Improve prediction accuracy by combining different models.
This 35-hour course in Quito covers deep neural network fundamentals, including CNNs, RNNs, and generative models like GANs. Participants gain hands-on experience with Theano and TensorFlow, learning to build, train, and deploy production-grade deep learning models for real-world applications.
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Testimonials (3)
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
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
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