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LO-1
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Explains the fundamental concepts of deep learning, the structure of artificial neural networks, and their learning processes. |
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LO-2
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Builds and implements basic deep learning models using the TensorFlow and/or PyTorch libraries. |
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LO-3
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Compares different deep learning architectures such as CNN, RNN, LSTM, and Transformer, and applies them to appropriate problems. |
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LO-4
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Analyzes deep learning methods in the context of big data, develops projects on real data sets, and interprets the results. |