Explore the diverse and powerful world of core generative AI. This course provides a comprehensive survey of the fundamental models that power modern AI, including Generative Adversarial Networks (GANs), autoregressive models, and diffusion models. You will build a strong foundation, understanding the unique architectures and training strategies for each, and compare essential frameworks like PyTorch and TensorFlow. The course then moves into hands-on implementation. You will learn to generate sequential data, such as time-series forecasts, using advanced autoregressive models in Azure AI Foundry. Next, you will master the art of high-fidelity image generation, using diffusion models to create and edit stunning visuals with techniques like inpainting and outpainting. Finally, you will learn to accelerate your development workflow by using Azure ML Designer, a visual, low-code environment for rapid prototyping. You will practice designing, building, evaluating, and preparing sophisticated model pipelines for real-world deployment. This course equips you not just with knowledge of different models, but with the practical skills to build and prototype them effectively on Azure.
What you'll learn
understanding of Generative Adversarial Networks (GANs)
knowledge of autoregressive models and diffusion models
ability to generate sequential data using advanced models
skills in high-fidelity image generation and manipulation
proficiency in using Azure ML Designer for model pipelines
Course objectives
provide a comprehensive survey of generative models
enable hands-on implementation of core generative techniques
develop practical skills for building and prototyping models on Azure