Online or onsite, instructor-led live Reinforcement Learning training courses demonstrate through interactive hands-on practice how to create and deploy a Reinforcement Learning system.
Reinforcement Learning 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 Reinforcement Learning training can be carried out locally on customer premises in Brussels or in NobleProg corporate training centers in Brussels.
NobleProg -- Your Local Training Provider
Brussels
Business Center Copernico Science14, Rue de la Science 14, Brussels, Belgium, 1040
Most of the European Union's Brussels-based institutions are located within its European Quarter, which is the unofficial nam...
Most of the European Union's Brussels-based institutions are located within its European Quarter, which is the unofficial name of the area corresponding to the approximate triangle between Brussels Park, Cinquantenaire Park and Leopold Park (with the European Parliament's hemicycle extending into the latter). The Commission and Council are located in the heart of this area near to the Schuman station at the Schuman roundabout on the Rue de la Loi. The European Parliament is located over the Brussels-Luxembourg station, next to Luxembourg Square.
The area, much of which was known as the Leopold Quarter for much of its history, was historically residential, an aspect which was rapidly lost as the institutions moved in, although the change from a residential area to a more office oriented one had already been underway for some time before the arrival of the European institutions. Historical and residential buildings, although still present, have been largely replaced by modern offices. These buildings were built not according to a high quality master plan or government initiative, but according to speculative private sector construction of office space, without which most buildings of the institutions would not have been built. However, due to Brussels's attempts to consolidate its position, there was large government investment in infrastructure in the quarter. Authorities are keen to stress that the previous chaotic development has ended, being replaced by planned architecture competitions and a master plan. Architect Benoit Moritz has argued that the area has been an elite enclave surrounded by poorer districts since the mid-19th century, and that the contrast today is comparable to an Indian city. However, he also said that the city has made progress over the last decade in mixing land uses, bringing in more businesses and residences, and that the institutions are more open to "interacting" with the city.
This instructor-led, live training in Brussels (online or onsite) is aimed at intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).By the end of this training, participants will be able to:
Understand the components and functionality of transformer models.
Optimize and fine-tune LLMs for specific tasks and applications.
Understand the core principles and methodologies of reinforcement learning.
Learn how reinforcement learning techniques can enhance the performance of LLMs.
This instructor-led, live training in Brussels (online or onsite) is aimed at developers and data scientists who wish to learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent.
By the end of this training, participants will be able to:
Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning.
Apply advanced Reinforcement Learning algorithms to solve real-world problems.
This instructor-led, live training in Brussels (online or onsite) is aimed at data scientists who wish to create and deploy a Reinforcement Learning system, capable of making decisions and solving real-world problems within an organization.
By the end of this training, participants will be able to:
Understand the relationships and differences between Reinforcement Learning and machine learning, deep learning, supervised and unsupervised learning.
Analyze a real-world problem and redefine it as Reinforcement Learning problem.
Implementing a solution to a real-world problem using Reinforcement Learning.
Understand the different algorithms available in Reinforcement Learning and select the most suitable one for the problem at hand.
This instructor-led, live training in Brussels (online or onsite) is aimed at data scientists who wish to go beyond traditional machine learning approaches to teach a computer program to figure out things (solve problems) without the use of labeled data and big data sets.
By the end of this training, participants will be able to:
Install and apply the libraries and programming language needed to implement Reinforcement Learning.
Create a software agent that is capable of learning through feedback instead of through supervised learning.
Program an agent to solve problems where decision making is sequential and finite.
Apply knowledge to design software that can learn in a way similar to how humans learn.
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