Miskolc

NobleProg Miskolc, Bencések útja 9-11, , Miskolc, hungary, 3519
Our conference rooms are located only 8 km away from the vibrant city center of Miskolc in the district of Tapolcafürdő. Ou...

Explore Our Courses

Deep Reinforcement Learning with Python

21 Hours
This instructor-led, live training in Borsod-Abaúj-Zemplén (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.
  • Build a Deep Learning Agent.
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Fundamentals of Reinforcement Learning

21 Hours
This instructor-led, live training in Borsod-Abaúj-Zemplén (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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Reinforcement Learning with Java

21 Hours
This instructor-led, live training in Borsod-Abaúj-Zemplén (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.
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Testimonials (10)

The training definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide. It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.

Terry Strachan - Exel Computer Systems plc
Course - OptaPlanner in Practice

examples and exercises

Kamil
Course - Introduction to Data Science and AI using Python

Machine Translated

The course is very interesting being the main focus nowdays

mohamed taher - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Ahmed was very interactive and didn’t mind answering any kind of questions Well presentation and smooth flow of the course

Mohamed Ghowaiba - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Helpful and good listener .. interactive

Ahmed El Kholy - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

All the information presented

Jose Victor - si
Course - Artificial Intelligence (AI) for Managers

The exercises and examples presented.

Marcos - si
Course - Artificial Intelligence (AI) for Managers

Machine Translated

Machine Learning Themes

Víctor Edgar - si
Course - Artificial Intelligence (AI) for Managers

The teacher's attitude

Ivonne Guadalupe Avendaño Hernandez - si
Course - Artificial Intelligence (AI) for Managers

Machine Translated

The concepts taught were clear, practical and help a lot in getting an idea of how to use this AI & ML topic.

Miguel - si
Course - Artificial Intelligence (AI) for Managers

Machine Translated

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