Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. Before you know it, you’ll be implementing an entire TinyML application.

Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.

Machine learning is amazing… and intimidating. How can computers do magical things like understand images or text? This training for programmers will dispel the magic and help you to build your own computer vision program, starting from scratch.

If you don't know the question, you probably won't get the answer right. This course is all about asking the right machine learning questions, modeling real-world situations as one of several well understood machine learning problems.

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Learn how to tune your model's hyperparameters to get the best predictive results.

Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning and neural networks.

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.