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Updated in [March 06th, 2023]

What skills and knowledge will you acquire during this course?
This course will provide learners with the skills and knowledge to build deep learning models with PyTorch. Learners will gain an understanding of the basics of PyTorch, such as Tensors and Gradients, as well as more advanced topics such as Linear Regression, Gradient Descent, Logistic Regression, Feedforward Neural Networks, and Training on GPUs. Additionally, learners will be able to explore more advanced topics such as Convolutional Neural Networks, Recurrent Neural Networks, Transfer Learning, and Generative Adversarial Networks.

How does this course contribute to professional growth?
This course provides a comprehensive introduction to deep learning using PyTorch, from the basics to advanced topics such as Generative Adverserial Networks and Image Captioning. It covers topics such as Tensors & Gradients, Linear Regression & Gradient Descent, Classification using Logistic Regression, and Feedforward Neural Networks & Training on GPUs. By taking this course, professionals can gain a better understanding of deep learning and its applications, as well as the skills to build and train deep learning models with PyTorch.

Is this course suitable for preparing further education?
This course is suitable for preparing further education in deep learning with PyTorch. It covers the basics of PyTorch, such as Tensors & Gradients, Linear Regression & Gradient Descent, and Classification using Logistic Regression, as well as more advanced topics such as Feedforward Neural Networks & Training on GPUs. Additionally, the course is updated on a weekly basis with new material, including CNNs, RNNs, transfer learning, and GANs.