![Deep Learning A-Z [2026]: DL, AI in Python & AWS + LLM Prize](https://img-c.udemycdn.com/course/750x422/1151632_de9b_3.jpg)
Learn to build and train Deep Learning models in Python from two Machine Learning & AI experts. Code templates included.
InstructorKirill Eremenko
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FreeThe curriculum follows a logical progression from Artificial Neural Networks through to AutoEncoders, including specialized modules for intuition and implementation.
Instruction includes practical paths for deploying models using AWS services such as SageMaker Canvas and Amazon Rekognition.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This spreadsheet outlines the course structure for Part 2, detailing specific modules on CNN intuition, building neural networks, and improving model performance.
This spreadsheet outlines the syllabus for advanced unsupervised learning topics, detailing sections on Boltzmann Machines and AutoEncoders with steps for intuition and implementation.
Course page displaying instructor bios and statistics, including review counts and student numbers highlighted by red circles.
Multiple signals suggest that code examples may no longer function correctly in current environments and certain models are no longer widely used. Note that these reviews were posted before the displayed update date, which does not prove a correction has occurred.
Multiple signals suggest that code examples may no longer function correctly in current environments and certain models are no longer widely used. Note that these reviews were posted before the displayed update date, which does not prove a correction has occurred.
The curriculum aligns well with the stated goals of introducing various deep learning architectures to those with basic math and Python knowledge.