Dive into autoencoders and regularization techniques. Learn how to build and implement autoencoders for unsupervised learning tasks, improving data representation and reducing overfitting.

Learn how to use transformer-based embeddings to automate content recommendations. Explore how deep learning models like BERT or GPT can be leveraged to enhance recommendation systems by understanding content and user preferences.

This course will teach you how you can build and train regression, classification, and forecasting models using Databricks AutoML. AutoML automates data preparation and model training thus allowing you to build models with little to no code.

Learn how to automate repetitive tasks using Large Language Models (LLMs). Streamline workflows, create bots, and enhance productivity with AI-driven automation.

Learn how to implement automated inspection systems using computer vision techniques, focusing on image processing and analysis for quality control.

This learning path is a brief introduction to a new AI paradigm called Machine Teaching for Autonomous AI. Machine Teaching uses the knowledge of subject matter experts to teach AI. It integrates known control methods for stable control, Machine Learning for advance perception, and Deep Reinforcement Learning for learning strategies and human-like decision making. It's AI integrated in industrial processes without disruption and providing real business value. It's validated in simulation, explainable that your experts can validate. Machine Teaching for Autonomous AI stores expert operators' skill set, enhancing and homogenizing expert operators' best performance, and/or efficiently training novices on the job when deployed as a Decision Support tool. It helps your company achieve new levels of optimization for competitiveness, profitability, and sustainability. It provides a robust innovation path for all areas of industrial processes and business with real ROI. At the end of this learning path, you'll be able to:

Learn how to prevent security vulnerabilities in generative AI applications. Understand common exploits and implement best practices to protect your AI-driven systems from potential risks.

Engage in a hands-on experience to learn reinforcement learning through autonomous racing simulations with AWS DeepRacer.

In this course, you get an overview of the concepts, terminology, and processes of the exciting field of machine learning!

Gain foundational knowledge of machine learning concepts and AWS services for building ML applications.

Join Joe Pringle, AWS for an inside perspective on how to understand machine learning and how to put it to work in your role.

Master AWS Sagemaker by Building Real World Projects