Rzeszów

RISE, Plac Wolności 13, Rzeszów, Poland, 35-073

The training room is located in the very heart of Rzeszow, making it easily accessible for participants. In the immediate vicinity, there are major public transportation hubs, such as city buses (MPK), railways (PKP), and long-distance buses (PKS), facilitating access from various parts of the city and beyond. Additionally, there is an underground parking garage at the Center Park gallery nearby, providing convenient parking for those using their own vehicles.

Głogów Małopolski

NobleProg , Strefowa 1, Głogów Małopolski, Poland, 36-060

The training room is located just 10 km southwest of Rzeszow, directly on the Rzeszow-Radom route, providing easy access from both cities. Additionally, its proximity to the A4 motorway and Jasionka airport facilitates transportation for both car travelers and those utilizing air transport.

Explore Our Courses

Large Language Models (LLMs) and Reinforcement Learning (RL)

 21 Hours
This instructor-led, live training in podkarpackie (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.
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Reinforcement Learning with Google Colab

 28 Hours
This instructor-led, live training in podkarpackie (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of reinforcement learning and its practical applications in AI development using Google Colab. By the end of this training, participants will be able to:
  • Understand the core concepts of reinforcement learning algorithms.
  • Implement reinforcement learning models using TensorFlow and OpenAI Gym.
  • Develop intelligent agents that learn through trial and error.
  • Optimize agents' performance using advanced techniques such as Q-learning and deep Q-networks (DQNs).
  • Train agents in simulated environments using OpenAI Gym.
  • Deploy reinforcement learning models for real-world applications.
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Deep Reinforcement Learning with Python

 21 Hours
This instructor-led, live training in podkarpackie (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 podkarpackie (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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Testimonials (1)

The training level was high. The instructor was not afraid to use mathematical formalisms.

Mateusz Soczewka - Santander Bank Polska S.A.

Course - Fundamentals of Reinforcement Learning

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