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

 21 Hours

This instructor-led, live training in Srbija (online or onsite) is designed for intermediate-level data scientists aiming to develop a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

By the conclusion 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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Advanced Model Optimization via Reinforcement Learning from Human Feedback (RLHF)

 14 Hours

This live, instructor-led training in Srbija (online or onsite) targets advanced machine learning engineers and AI researchers aiming to utilize RLHF for the fine-tuning of large AI models to achieve enhanced performance, safety, and alignment.

By the end of this training, participants will be able to:

  • Comprehend the theoretical underpinnings of RLHF and its significance in modern AI advancement.
  • Construct reward models based on human input to guide reinforcement learning cycles.
  • Refine large language models using RLHF techniques to align results with human expectations.
  • Apply best practices for scaling RLHF processes in production-grade AI environments.
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Reinforcement Learning with Google Colab

 28 Hours

This live, instructor-led training, available Srbija (online or on-site), is tailored for advanced professionals seeking to deepen their expertise in reinforcement learning and its practical application in AI development using Google Colab.

By the conclusion of this training, participants will be able to:

  • Grasp 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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Duboko jачe učenje sa Pythonom

 21 Hours
Ova usmerena obuka u Srbija pokriva teorijske osnove i praktičnu implementaciju dubokog jачeg učenja koristeći Python. Učesnici će izgraditi i obučavati DRL agente koristeći TensorFlow ili PyTorch, primenjujući ključne algoritme kao što su DQN i PPO za rešavanje kompleksnih stvarnih problema.
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Upcoming Courses

Advanced Model Optimization via Reinforcement Learning from Human Feedback (RLHF)

2026-12-10 09:30
14 hours
Green Heart Complex
338 EUR (Online)
338 EUR (Classroom)

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

2026-12-24 09:30
21 hours
Green Heart Complex
506 EUR (Online)
506 EUR (Classroom)

Reinforcement Learning with Google Colab

2027-01-07 09:30
28 hours
Green Heart Complex
675 EUR (Online)
675 EUR (Classroom)

Advanced Model Optimization via Reinforcement Learning from Human Feedback (RLHF)

2027-01-21 09:30
14 hours
Green Heart Complex
338 EUR (Online)
338 EUR (Classroom)

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