courses
Generative AI describes technologies that are used to generate new content based on a variety of inputs. In recent time, Generative AI involves the use of neural networks to identify patterns and structures within existing data to generate new content. In this course, you will learn Generative AI concepts, applications, as well as the challenges […]
Generative AI Explained Read More »
This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for,
Transformer Models and BERT Model Read More »
This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question
Attention Mechanism Free Course Read More »
This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll
Encoder-Decoder Architecture Free Course Read More »
.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.
Introduction to Image Generation-Free Course Read More »
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. When you complete this course, you can earn the badge displayed here! View all the badges you have earned by visiting your profile
Introduction to Responsible AI-Free Course Read More »
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. When you complete this course, you can
Introduction to Large Language Models Read More »
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. When you complete this course, you can earn the badge displayed here! View all
Introduction to Generative AI Read More »
About this course Skip About this course Every single minute, computers across the world collect millions of gigabytes of data. What can you do to make sense of this mountain of data? How do data scientists use this data for the applications that power our modern world? Start Now
Introduction to Data Science with Python by Harvard University Read More »
