Whether delivered online or in-person, our live instructor-led Neural Network training courses emphasize interactive dialogue and practical application. Participants learn to build Neural Networks using a suite of predominantly open-source toolkits and libraries, while also exploring how to leverage advanced hardware such as GPUs and optimization techniques that involve distributed computing and big data. Our curriculum is grounded in widely adopted programming languages like Python, Java, and R, supported by robust libraries including TensorFlow, Torch, Caffe, and Theano. These courses balance theoretical foundations with real-world implementation, covering various architectures such as Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN).
Neural Network training is offered as either "online live training" or "onsite live training". The online option, also known as "remote live training", is conducted through an interactive remote desktop. Onsite sessions can be hosted at your customer premises in Varna or at NobleProg’s corporate training centers in Varna.
The "Central Point" complex offers quick access to main roads leading to the airport, the northern and southern resorts and the Varna - Sofia and Varna - Burgas highways.
This instructor-led, live training in Varna (online or onsite) is designed for advanced professionals who wish to explore state-of-the-art XAI techniques for deep learning models, focusing on the development of interpretable AI systems.
Upon completion of this training, participants will be able to:
Grasp the challenges associated with explainability in deep learning.
Apply advanced XAI techniques to neural networks.
Interpret the decisions generated by deep learning models.
Assess the balance between model performance and transparency.
This hands-on training in Varna enables developers to construct AI models using Python from first principles. You will gain proficiency in supervised learning, neural networks, and unsupervised methods by leveraging scikit-learn and Apache Spark. The course emphasizes practical Jupyter exercises designed for real-world problem-solving.
This instructor-led training in Varna delves into the theoretical basis and practical application of Deep Reinforcement Learning with Python. Participants will construct and train DRL agents using TensorFlow or PyTorch, leveraging key algorithms like DQN and PPO to address complex real-world challenges.
A foundational training module in Varna that covers AI fundamentals, from intelligent agents to machine learning. It prepares executives and architects to evaluate emerging AI trends, incorporate practical solutions, and enhance business agility through automated strategies.
Discover how Machine Learning and Deep Learning are reshaping the automotive landscape. This Varna course explores fundamental concepts ranging from simple automation to autonomous decision-making, featuring neural networks and practical TensorFlow examples tailored for real-world applications.
This three-day intensive on Varna integrates the theoretical underpinnings with practical applications of Artificial Neural Networks, Machine Learning, and Deep Learning. Attendees will examine various network architectures, learning algorithms, and the associated mathematical foundations, progressing from foundational perceptrons to sophisticated deep learning methodologies.
This instructor-led, live training in Varna (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 35-hour course in Varna delves into the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Participants will gain practical experience with Theano and TensorFlow, acquiring the skills to build, train, and deploy production-grade deep learning models for real-world scenarios.
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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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