Available either online or onsite, our instructor-led live Deep Learning (DL) training courses provide a practical, hands-on introduction to the core principles and real-world applications of Deep Learning. The curriculum explores key areas including deep machine learning, deep structured learning, and hierarchical learning.
These sessions are offered as "online live training" or "onsite live training". Online live training (also referred to as "remote live training") utilizes an interactive, remote desktop environment. Onsite live training takes place locally at client premises in Abu Dhabi or within NobleProg corporate training centers in Abu Dhabi.
NobleProg -- Your Local Training Provider
Park Rotana Complex
2, Butti Biltahina Al Muhairi St, Abu Dhabi, United Arab Emirates
Situated within the Park Complex and adjacent to TwoFour54 and Khalifa Park. Park Rotana is 15 minutes drive from Abu Dhabi International Airport and Yas Island.
Driving directions from Abu Dhabi International Airport:
Drive towards Abu Dhabi by highway No. E 10, Keep driving straight after passing the “Al Raha mall”. Follow the signage “Sheikh Zayed Bridge” to drive through the bridge, Keep in the right lane when you finish the bridge. You are now driving on “Salam / Eastern” road. Take the exit “Khalifa Park & Ministries Complex” from extreme right lane to make a “U turn” over the underpass, Follow the signal “Park Rotana Complex” and take right to the roundabout. After it, turn left in the roundabout and drive straight until you reach Park Rotana.
Radisson Blu Hotel & Resort
2, Corniche St, Abu Dhabi, United Arab Emirates
Our location provides a memorable setting for both business and social events near local attractions and beaches on the Arabian Gulf. Rely on Radisson Blu to deliver a flawless meeting experience incorporating elements like audiovisual equipment and customized menus, as well as free Wi-Fi. Our stunning ballroom (with adjoining terrace) is divisible into three separate areas with private entrances for a truly impressive events space
This instructor-led live training offered in Abu Dhabi (online or onsite) caters to intermediate-level developers, data scientists, and AI practitioners aiming to harness 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 Abu Dhabi (online or onsite) is designed for advanced professionals aiming to deepen their grasp of computer vision and explore TensorFlow’s capabilities for building advanced vision models using Google Colab.
By the conclusion 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 Abu Dhabi (online or onsite) is aimed at 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 Abu Dhabi (online or onsite) is aimed at advanced-level professionals who wish to specialize in cutting-edge deep learning techniques for NLU.
By the end of this training, participants will be able to:
Understand the key differences between NLU and NLP models.
Apply advanced deep learning techniques to NLU tasks.
Explore deep architectures such as transformers and attention mechanisms.
Leverage future trends in NLU for building sophisticated AI systems.
This instructor-led, live training in Abu Dhabi (online or onsite) is designed for advanced-level 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 instructor-led live training in Abu Dhabi (online or onsite) is designed for intermediate to advanced data scientists, machine learning engineers, deep learning researchers, and computer vision professionals aiming to expand 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 for better model performance and generalization.
Integrate Stable Diffusion with other deep learning frameworks and tools
This instructor-led, live training in Abu Dhabi (online or onsite) is designed for advanced professionals seeking to leverage AI techniques to revolutionize drug discovery and development workflows.
Upon completion of this training, participants will be able to:
Comprehend the pivotal role of AI in drug discovery and development.
Utilize machine learning methods to predict molecular properties and interactions.
Employ deep learning models for virtual screening and lead optimization.
Incorporate AI-driven strategies into clinical trial processes.
This instructor-led, live training (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 Abu Dhabi (online or onsite) targets beginner to intermediate-level developers seeking to apply Large Language Models to various natural language tasks.
By the end of this course, participants will be able to:
Set up a development environment that includes a popular LLM.
Create a basic LLM and fine-tune it on a custom dataset.
Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
This instructor-led live training (available online or onsite) is designed for 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 workings in image generation.
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 Abu Dhabi, participants will master the most relevant and cutting-edge machine learning techniques in Python. This is achieved by building a series of demonstration applications that process image, music, text, and financial data.
Upon completing this training, participants will be equipped to:
Implement machine learning algorithms and techniques to address complex problems.
Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
Maximize the potential of Python algorithms.
Utilize libraries and packages such as NumPy and Theano.
This hands-on program in Abu Dhabi enables developers to engineer AI models from scratch with Python. Participants will gain proficiency in supervised learning, neural networks, and unsupervised methods through the use of scikit-learn and Apache Spark. The curriculum emphasizes practical Jupyter exercises designed for real-world application.
This instructor-led training in Abu Dhabi explores the theoretical underpinnings and practical application of Deep Reinforcement Learning using Python. Participants will develop and train DRL agents with TensorFlow or PyTorch, leveraging key algorithms like DQN and PPO to address complex real-world challenges.
A foundational course in Abu Dhabi that covers AI principles, ranging from intelligent agents to machine learning. It prepares executives and architects to evaluate emerging AI trends, incorporate practical solutions, and boost business agility via automated strategies.
Discover how Machine Learning and Deep Learning are reshaping the automotive landscape. This Abu Dhabi course explores fundamental concepts, evolving from basic automation to autonomous decision-making. It covers neural networks and provides practical TensorFlow examples tailored for real-world implementations.
This three-day program in Abu Dhabi delves into the theoretical underpinnings and practical applications of Artificial Neural Networks, Machine Learning, and Deep Learning. Attendees will examine network architectures, learning mechanisms, and the mathematical basis of these systems, progressing from fundamental perceptrons to sophisticated deep learning techniques.
This instructor-led, live training in Abu Dhabi (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 live, instructor-led course conducted in Abu Dhabi enables participants to apply Python NLP libraries by developing an application that processes image sets and generates descriptive captions.
Upon completion, participants will be able to:
Architect and implement Deep Learning solutions for NLP using Python libraries.
Develop Python scripts that analyze large-scale image collections to extract relevant keywords.
Write Python code that synthesizes descriptive captions based on the identified keywords.
This instructor-led live training in Abu Dhabi (online or on-site) is designed for software developers, data analysts, and technical experts aiming to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models tailored for computer vision, natural language processing, and multimodal applications.
This instructor-led live training in Abu Dhabi (online or onsite) is tailored for data scientists aiming to apply TensorFlow to the analysis of potential fraud data.
By the end of this training, participants will be able to:
Construct a fraud detection model using Python and TensorFlow.
Build linear regression models to predict fraud.
Develop an end-to-end AI application for analyzing fraud data.
During 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 Abu Dhabi (available online or onsite) is tailored for developers and data scientists looking to utilize TensorFlow 2.x to build predictors, classifiers, generative models, neural networks, and more.
Upon completion 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 35-hour course in Abu Dhabi delves into the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Learners will acquire practical experience with Theano and TensorFlow, gaining the skills to build, train, and deploy production-grade deep learning models for real-world scenarios.
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Testimonials (5)
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
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
Nola - Laramie County Community College
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
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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