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DeepSeek-R1 Course

DeepSeek-R1 Course

Free

The DeepSeek course is an advanced training program aimed at professionals and enthusiasts in the fields of artificial intelligence, machine learning, and data science. With both a practical and theoretical approach, DeepSeek delves deeply into deep learning techniques, handling large volumes of data, and predictive modeling. Participants learn how to implement neural networks, work with popular frameworks like TensorFlow and PyTorch, and develop innovative solutions for complex problems. The course also covers topics such as computer vision, natural language processing (NLP), convolutional neural networks (CNN), recurrent neural networks (RNN), and advanced optimization techniques. Additionally, DeepSeek emphasizes practical applications in areas such as automation, predictive analytics, pattern recognition, and generative AI. By the end of the course, students are equipped to build robust models, optimize algorithms, and apply their knowledge to solve real-world challenges across various industries.

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Has discount
Expiry period Lifetime
Made in English
Last updated at Sun Feb 2025
Level
Advanced
Total lectures 1
Total quizzes 0
Total duration 01:30:56 Hours
Total enrolment 30
Number of reviews 1
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Short description The DeepSeek course is an advanced training program aimed at professionals and enthusiasts in the fields of artificial intelligence, machine learning, and data science. With both a practical and theoretical approach, DeepSeek delves deeply into deep learning techniques, handling large volumes of data, and predictive modeling. Participants learn how to implement neural networks, work with popular frameworks like TensorFlow and PyTorch, and develop innovative solutions for complex problems. The course also covers topics such as computer vision, natural language processing (NLP), convolutional neural networks (CNN), recurrent neural networks (RNN), and advanced optimization techniques. Additionally, DeepSeek emphasizes practical applications in areas such as automation, predictive analytics, pattern recognition, and generative AI. By the end of the course, students are equipped to build robust models, optimize algorithms, and apply their knowledge to solve real-world challenges across various industries.
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