Whether you prefer remote participation or face-to-face engagement, our instructor-led live Deep Learning (DL) programs offer practical, hands-on experiences that explore the core principles and real-world applications of the field. Key topics include deep machine learning, deep structured learning, and hierarchical learning.
Deep Learning instruction is offered as either "online live training" or "onsite live training". The online option, also referred to as "remote live training", facilitates interaction through a remote desktop session. Conversely, onsite training can be hosted at your premises in Durban or within NobleProg’s dedicated corporate training facilities in Durban.
NobleProg – Your Regional Training Partner
Garden Court South Beach
Durban, South Africa
Way to get there
From Durban city centre: follow the beachfront/Marine Parade south toward South Beach.
By car/taxi: give the driver the address 73 O.R. Tambo Parade, South Beach, Durban 4001.
From King Shaka International Airport: the hotel is roughly 30 km ;from the airport.
This instructor-led live training in Durban (online or onsite) targets intermediate-level developers, data scientists, and AI practitioners who want to utilise TensorFlow Lite for Edge AI applications.
By the end of this training, participants will be able to:
Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
Develop and optimise AI models using TensorFlow Lite.
Deploy TensorFlow Lite models on various edge devices.
Utilise tools and techniques for model conversion and optimisation.
Implement practical Edge AI applications using TensorFlow Lite.
This instructor-led, live training in Durban (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.
By the end of this training, participants will be able to:
Construct and train convolutional neural networks (CNNs) using TensorFlow.
Utilise 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.
Apply transfer learning to enhance the performance of CNN models.
Visualise and interpret the results of image classification models.
This instructor-led, live training in Durban (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 Durban (online or onsite) is aimed at advanced-level professionals who wish to specialise 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.
Delivered as instructor-led live training in Durban (available online or on-site), this programme is designed for advanced professionals keen to explore state-of-the-art XAI techniques for deep learning models, with a strong emphasis on building interpretable AI systems.
Upon completion of this training, participants will be able to:
Grasp the challenges associated with 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 Durban (online or on-site) is designed for intermediate to advanced data scientists, machine learning engineers, deep learning researchers, and computer vision specialists who aim to expand their skills in deep learning for text-to-image generation.
By the end of this course, participants will be able to:
Understand advanced deep learning architectures and techniques for text-to-image generation.
Implement complex models and optimisations for high-quality image synthesis.
Optimise performance and scalability for large datasets and intricate models.
Tune hyperparameters to enhance model performance and generalisation.
Integrate Stable Diffusion with other deep learning frameworks and tools.
This instructor-led, live training in Durban (online or onsite) is aimed at advanced-level professionals who wish to leverage AI techniques to revolutionize drug discovery and development processes.
By the end of this training, participants will be able to:
Understand the role of AI in drug discovery and development.
Apply machine learning techniques to predict molecular properties and interactions.
Use deep learning models for virtual screening and lead optimization.
Integrate AI-driven approaches into the clinical trial process.
This instructor-led, live training in Durban (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 Durban (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.
By the end of this training, 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 in (online or onsite) is aimed at 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 how it works for 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 Durban, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data.
By the end of this training, participants will be able to:
Implement machine learning algorithms and techniques for solving complex problems.
Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
Push Python algorithms to their maximum potential.
Use libraries and packages such as NumPy and Theano.
This practical training in Durban empowers programmers to construct AI models using Python. You will gain proficiency in supervised learning, neural networks, and unsupervised techniques through the use of scikit-learn and Apache Spark. The focus is on hands-on exercises in Jupyter notebooks designed to solve real-world problems.
This instructor-led training in Durban 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.
A foundational training in Durban that delves into AI fundamentals, ranging from intelligent agents to machine learning. It empowers executives and architects to evaluate emerging AI trends, integrate practical solutions, and boost business agility through automated strategies.
Investigate how Machine Learning and Deep Learning are reshaping the automotive industry. This Durban programme outlines key concepts spanning from basic automation to autonomous decision-making, featuring neural networks and practical TensorFlow examples for real-world implementation.
This three-day programme focused on Durban 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 techniques.
This instructor-led, live training in Durban (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 instructor-led, live training in Durban (online or onsite) is aimed at software developers, data analysts, and technical professionals who wish to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.
This instructor-led live training in Durban (available online or onsite) is targeted at data scientists who wish to employ TensorFlow to analyse potential fraud data.
By the end of this training, participants will be able to:
Create a fraud detection model in Python and TensorFlow.
Build linear regressions and linear regression models to predict fraud.
Develop an end-to-end AI application for analyzing fraud data.
In this instructor-led, live training, attendees will discover how to leverage Matlab to design, construct, and visualise a convolutional neural network for image recognition.
Upon completion of this training, participants will be capable of:
Constructing a deep learning model
Automating the data labelling process
Utilising models from Caffe and TensorFlow-Keras
Training data across multiple GPUs, cloud environments, or clusters
Target Audience
Developers
Engineers
Domain experts
Course Format
A blend of lectures, discussions, exercises, and extensive hands-on practice
This instructor-led live training in Durban (delivered online or on-site) is designed for developers and data scientists seeking to utilise TensorFlow 2.x to build sophisticated predictors, classifiers, generative models, and neural networks.
By the end of this programme, participants will have the capability to:
Install and configure TensorFlow 2.x effectively.
Comprehend the benefits TensorFlow 2.x offers over earlier versions.
Construct deep learning models.
Implement an advanced image classifier.
Deploy deep learning models to cloud environments, mobile applications, and IoT devices.
This 35-hour course in Durban 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 (5)
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
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
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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