Available as online or onsite, instructor-led live courses, these Neural Network programs use interactive discussions and hands-on practice to show how to build Neural Networks using a range of open-source toolkits and libraries. The training also covers leveraging advanced hardware, such as GPUs, and optimization techniques related to distributed computing and big data. These courses are built around widely used programming languages like Python, Java, and R, alongside powerful libraries such as TensorFlow, Torch, Caffe, and Theano. The curriculum balances theory with practical implementation, covering various architectures including Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN).
Neural Network training can be delivered either as "online live training" or "onsite live training." The online format, also known as "remote live training," is conducted through an interactive remote desktop environment. Onsite live training can be provided at client locations in Östergötland or at NobleProg corporate training centers in Östergötland.
NobleProg -- Your Local Training Provider
Linköping
NobleProg classroom in Scandic Linköping, Gamla Tanneforsvägen 51, Linköping, sweden, 582 54
Scandic Linköping City is a modern conference place. It's located in central Linköping and also close to Linkoping Cathedral and Linköping Garden Society. Linköping Airport is just a 5-minute car drive away from the conference centre. Other famous landmarks such as the Swedish Airforce Museum and the Old Town is only a 10-minute drive as well.
This instructor-led, live training in Östergötland (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.
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 hands-on training in Östergötland empowers programmers to construct AI models from the ground up using Python. You will gain proficiency in supervised learning, neural networks, and unsupervised techniques through the use of scikit-learn and Apache Spark. The course emphasizes practical Jupyter-based exercises aimed at solving complex, real-world problems.
This instructor-led program in Östergötland delves into both the theoretical basis and practical application of Deep Reinforcement Learning via Python. Learners will construct and train DRL agents with TensorFlow or PyTorch, implementing essential algorithms such as DQN and PPO to tackle intricate real-world challenges.
An introductory course in Östergötland that covers AI fundamentals, ranging from intelligent agents to machine learning. It prepares executives and architects to evaluate emerging AI trends, incorporate practical solutions, and boost business agility through automated strategies.
Discover the transformative impact of Machine Learning and Deep Learning on the automotive industry. This Östergötland course explores fundamental concepts, bridging the gap from simple automation to autonomous decision-making, and includes neural network theory alongside practical TensorFlow examples for real-world deployment.
This three-day program in Östergötland 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 foundations, progressing from fundamental perceptrons to sophisticated deep learning methodologies.
This instructor-led, live training in Östergötland (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 on Östergötland delves into the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models like GANs. Participants will gain practical experience using Theano and TensorFlow, learning how 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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