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Intermediate
Artificial Intelligence & Machine Learning
en
Deep Learning
Udacity
Platform
· California, USA
About this course
Build foundational skills in deep learning by designing and training neural networks to solve complex real-world problems. You’ll begin with the essentials of neural networks, advancing to specialized architectures like Convolutional and Recurrent Neural Networks, along with Transformers, Generative Adversarial Networks and Diffusion Models. Through projects, create models for applications such as image classification, Q&A, and CAPTCHA image generation, gaining hands-on experience with PyTorch and advanced training techniques. Ideal for those aiming to harness the potential of deep learning, this experience prepares you to tackle AI challenges across various domains.
Prerequisite Skills
Skills you should have before taking this course
PyTorch
Basic calculus
Pandas
Intermediate Python
Intermediate Python programming
Vectors
Skills Gained
Skills you will develop by completing this course
PyTorch
Generative adversarial networks
GAN training optimization
U-Net
Generative AI fluency
Diffusion model sampling
Generator network implementation
Deep convolutional GAN architecture
PyTorch for deep learning
Transformers
Convolutional neural networks (CNNs)
Recurrent neural networks (RNNs)