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 training can be carried out locally on customer premises in Glasgow or in NobleProg corporate training centers in Glasgow.
NobleProg -- Your Local Training Provider
Glasgow
69 Buchanan St, Glasgow, united kingdom, G1 3HL
The Buchanan Street Centre is located in the heart of Glasgow, in Scotland's most famous shopping and retail district. A major feature of this stunning large Victorian building is the impressive sandstone entrance archway giving access to four floors. Glasgow's fantastic array of shops, hotels, restaurants and bars are on the doorstep and Buchanan Street itself is home to a number of exclusive shops and recently won the Academy of Urbanism 'Great Street Award'. One of the fastest growing cities in the UK, Glasgow is Scotland's largest urban economy and is dominated by financial and business services, public administration, health and retail. It is one of Europe's 16 largest financial centres with a growing number of 'blue-chip' financial sector companies establishing significant operations or headquarters in the city. It also forms the western part of Scotland's 'Silicon Glen' hi-tech sector.
This instructor-led, live training in Glasgow (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 Glasgow 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 Glasgow 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 Glasgow 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 Glasgow 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 Glasgow 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 Glasgow (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 introduction covers the basics of neural networks in Glasgow, exploring AI fundamentals, neuron concepts, activation functions, and network construction. Participants learn backpropagation, training algorithms, and real-world applications like stock prediction.
This 35-hour course in Glasgow 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 (4)
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
It felt like we were going through directly relevant information at a good pace (i.e. no filler material)
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Introduction to the use of neural networks
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
Provisional Upcoming Courses (Contact Us For More Information)
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