In this capstone project, you'll use either Keras or PyTorch to develop, train, and test a Deep Learning model. Load and preprocess data for a real problem, build the model and then validate it.

New to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using thepopular Keras library.

This course is the second part of a two-part course on how to develop Deep Learning models using Pytorch.

Much of theworld's data is unstructured. Think images, sound, and textual data. Learn how to apply Deep Learning with TensorFlow to this type of data to solve real-world problems.

This course focuses on the core concepts and models of generative AI, including deep learning and large language models. It covers the concept of foundation models and the capabilities of pre-trained models and platforms for AI application development.

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

Training complex deep learning models with large datasets takes along time. In this course, you will learn how to use accelerated GPU hardware to overcome the scalability problem in deep learning.

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Explore Image Representation and Processing to learn transforming images for AI and computer vision tasks efficiently.

Many of the millions of digital images we're generating need interpretation, but there aren't enough human eyes for the task. This course will teach you how to use Python libraries and deep learning models to automate image segmentation.

Image recognition is used in a wide variety of ways in our daily lives. This course will teach you how to tune and implement convolutional neural networks in order to implement image recognition and classification on a business case.

Time series analysis is one of the more difficult and confusing aspects of data science. This course will teach you how to use TensorFlow with time series data and generate high performing forecasts and predictions.