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Learn about the basics of Generative AI and its applications in this beginner-level microlearning course. It focuses on differentiating Generative AI from traditional machine learning techniques. Estimated completion time: 45 minutes
This microlearning course covers large language models (LLM), their use cases, and how to improve LLM performance through prompt tuning. It also introduces Google tools for developing Gen AI apps. Estimated completion time: 45 minutes.
This microlearning course covers responsible AI, its significance, and Google's implementation of responsible AI in its products. It also introduces Google's 7 AI principles.
Earn a skill badge by completing the Intro to Generative AI, Intro to Large Language Models, and Intro to Responsible AI courses. Passing the final quiz demonstrates understanding of foundational concepts in generative AI.
Earn a skill badge by completing the Intro to Generative AI, Intro to Large Language Models, and Intro to Responsible AI courses. Passing the final quiz demonstrates understanding of foundational concepts in generative AI.
Course covers encoder-decoder for sequence-to-sequence tasks like translation, summarization, and QA. Covers components, training, serving, and simple poetry generation in TensorFlow.
This course teaches the attention mechanism which improves machine learning tasks like translation, summarization, and question-answering.
This course covers the Transformer architecture and the BERT model and explains the self-attention mechanism and its role in building BERT. It discusses BERT's applications in text classification, question answering, and natural language inference.
Learn to create an image captioning model using deep learning. Understand the components and train your model to generate captions for images.
The course introduces Generative AI Studio on Vertex AI, a tool for creating customized generative AI models. It covers features, options, and usage through demos and concludes with a quiz to test understanding.