1. Introduction to Generative AI
This is an introductory-level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine-learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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2. Introduction to Large Language Models
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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3. Introduction to Generative AI Studio
This course introduces Generative AI Studio, a product on Vertex AI, that helps you prototype and customize generative AI models so you can use their capabilities in your applications. In this course, you learn what Generative AI Studio is, its features and options, and how to use it by walking through demos of the product. In the end, you will have a quiz to test your knowledge.
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4. Introduction to Image Generation
This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics.
Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
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5. Introduction to Responsible AI
This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it’s important, and how Google implements responsible AI in their products. It also introduces Google’s 7 AI principles.
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6. Create Image Captioning Models
This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images.
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7. ML Pipelines on Google Cloud
In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud.
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8. Applying Machine Learning to Your Data with Google Cloud
In this course, we define what machine learning is and how it can benefit your business. You’ll see a few demos of ML in action and learn key ML terms like instances, features, and labels.
In the interactive labs, you will practice invoking the pre-trained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
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