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A new revolution is here

Build y optimizes models from IA that learn from your environment.

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    PROGRAM SPECIALIZED

    LEARNING REINFORCED

    This 30-hour course offers a comprehensive immersion in reinforced learning (RL), a branch of machine learning focused on sequential decision making. Throughout the course, fundamental concepts to advanced approaches based on deep learning will be addressed. Students will learn how to implement RL algorithms using frameworks such as Stable Baselines3 (SB3) and apply them in simulated and real environments in areas such as robotics, video games, finance and industrial automation.

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    Teaching hours: 30h.

    Online live

    Language: Spanish

    Support: 12 months

    Learning Reinforced

    OBJECTIVE

    Understand the fundamentals of reinforced learning and explore key concepts such as exploration vs. exploitation, action policies, rewards and value functions.

    MODALITY

    Online live.

    DURATION

    30h.

    SUPPORT

    By mail for 12 months.

    1.200,00€ / VAT includedCOMPRAR

    Objectives

    Understand the fundamentals from learning reinforced.

    Explore key concepts such as exploration vs. exploitation, action policies, rewards and value functions.

    Develop skills at methods classics from RL.

    Analyze Markov decision processes and the Bellman equation as the basis of RL.

    Master Deep Q-learning (DQL) y your implementation at problems complexes.

    Understand the integration of deep neural networks in Q-learning to cope with large state spaces.

    Explore techniques advanced from DQL for optimization y improvements.

    Learn about techniques such as prioritized experience replay and dueling networks.

    Design y create environments custom for learning reinforced.

    Apply key considerations when modeling environments, defining appropriate rewards and states.

    Acquire experience practice at the implementation y optimization from algorithms from RL.

    Participate in hands-on workshops to design, optimize and test RL algorithms in simulations and real-world applications.

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    PROVIDED BY

    Valero Laparra

    D. in Artificial Intelligence, specializing in machine learning and generative models, Valero has more than a decade of experience in research and development of advanced deep learning algorithms.
    He is currently Professor and Researcher at the University of Valencia, where he leads projects in areas such as deep neural networks and unsupervised learning. He has worked on practical applications of generative models in areas such as computer vision, image generation and sequential data processing.
    His experience spans both academia and industry, and he has published numerous articles in prestigious journals on artificial intelligence. During this course, Valero will provide a comprehensive and practical overview of generative learning, guiding students in the implementation of state-of-the-art techniques.

    Domina the learning reinforced y create agents smart capable from take decisions at environments complexes.

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    Learn effectively and act with impact.

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    Official Certifications

    By completing our programs you will have the opportunity to obtain an official certification that will help you open doors in the professional world.

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    Questions Frequent

    No, our programs are designed to suit different levels of experience. We offer courses for both beginners who wish to enter the world of AI, as well as advanced professionals looking to specialize in specific areas of this technology.

    Yes, by completing any of our programs you will receive an official certification recognized at a professional level, which will validate your AI skills and knowledge, helping you stand out in the job market.

    Yes, all of our courses are fully online, allowing you to access the content at any time and from anywhere. In addition, you will have access to real-time tutoring and support to ensure a complete learning experience.

    It depends on the course you choose. Some programs are designed for beginners with no prior technical knowledge, while others require a background in programming or data science. Each course clearly states the entry requirements so you can choose the one that best suits you.

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