Available online or on-site, these instructor-led TensorFlow training courses combine interactive discussions with practical exercises. They demonstrate how to utilize the TensorFlow system to advance machine learning research, while also showing how to seamlessly move from research prototypes to production-ready systems.
TensorFlow training can be delivered as either "online live training" or "onsite live training". Online live training (also known as "remote live training") is conducted via an interactive remote desktop. Onsite live training takes place either at your customer premises in Copenhagen or at NobleProg’s corporate training centres in Copenhagen.
You can also take bus 26 or 7A and get off around Vesterbros Torv; from there it is a short walk.
By bus
Useful nearby stops include:
Vesterbros Torv (Vesterbrogade) — about 1 minute from the area.
Frederiksberg Allé (Vesterbrogade) — nearby.
Trommesalen (Vesterbrogade) — nearby.
Bus 26 and 7A serve the Vesterbrogade corridor.
København, Copenhagen
NobleProg København, Bredgade 37, København K, denmark, 1260
Near Amalienborg Palace & Royal Theatre.
If you arrive by train
If you arrive at Copenhagen Central Station (København H):
Walk to København H Metro.
Take the M3 or M4 metro toward Kongens Nytorv.
Get off at Kongens Nytorv.
Walk north toward Nyhavn, then continue along Bredgade.
Bredgade 37 is about 500 m / 6 minutes' walk from Kongens Nytorv.
Another easy option
Marmorkirken (Marble Church) Metro Station is also very close to Bredgade 37. The nearby Bredgade area is about 2 minutes' walk from Marmorkirken station.
By bus
There are bus stops around Dronningens Tværgade / Bredgade, so you can also travel by bus and walk the final few minutes.
This instructor-led live training in Copenhagen (available online or on-site) is designed for advanced professionals aiming to refine their computer vision knowledge and utilize TensorFlow's capabilities for building sophisticated vision models through Google Colab.
By the end of this training, participants will be able to:
Construct 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, delivered in Copenhagen (either online or on-site), is designed for intermediate-level data scientists and developers seeking to master deep learning techniques within the Google Colab environment.
By the end of the session, participants will have acquired the skills to:
Set up and maneuver through Google Colab for deep learning initiatives.
Comprehend the basic principles of neural networks.
Construct deep learning models using TensorFlow.
Train and evaluate deep learning models.
Apply advanced TensorFlow features for deep learning.
This instructor-led, live training is delivered in Copenhagen (online or on-site) and is targeted at data scientists who aim to utilize TensorFlow for analyzing potential fraud data.
Upon completion, participants will be equipped to:
Develop a fraud detection model using Python and TensorFlow.
Construct linear regression models to effectively predict fraudulent behavior.
Engineer a comprehensive, end-to-end AI application tailored for fraud data analysis.
This instructor-led live training, offered online or on-site at Copenhagen, is designed for developers and data scientists who aim to utilize TensorFlow 2.x for building predictors, classifiers, generative models, neural networks, and more.
By the conclusion of this program, participants will be capable of:
Installing and configuring TensorFlow 2.x.
Understanding the benefits TensorFlow 2.x provides over previous iterations.
Building deep learning models.
Implementing an advanced image classifier.
Deploying deep learning models to cloud environments, mobile devices, and IoT systems.
This 35-hour course in Copenhagen explores the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Learners will gain practical, hands-on experience with Theano and TensorFlow, mastering how to build, train, and deploy production-grade deep learning models for real-world applications.
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Testimonials (1)
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
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