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Explore the fundamentals of Generative AI, its applications, and how it differs from traditional machine learning, with an introduction to Google's development tools.
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.
Learn to effectively use Gmail: compose messages, organize with labels, customize settings, manage contacts, and utilize advanced search and filtering for improved productivity.
Learn advanced Google Sheets: themes, conditional formatting, formulas, data validation, visualization, pivot tables, macros, and integration with Google Forms for efficient data analysis and reporting.
Learn to create, edit, and collaborate on spreadsheets with Google Sheets. Master data management, formatting, formulas, charts, and sharing features for efficient cloud-based spreadsheet work.
Explore large language models, their applications, and prompt tuning techniques. Learn to develop Gen AI apps using Google tools in this concise introduction.
Master Google Calendar to efficiently schedule, manage events, and collaborate with teams. Learn customization, sharing, and advanced features for optimal productivity.
Leverage Google Earth Engine to analyze petabytes of Earth Observation data, gaining insights for environmental research in forestry, agriculture, water, and sustainability.
Explore the encoder-decoder architecture for sequence-to-sequence tasks, learning its components, training, and implementation in TensorFlow for poetry generation.
Service level indicators (SLIs) and service level objectives (SLOs) are fundamental tools for measuring and managing reliability. In this course, students learn approaches for devising appropriate SLIs and SLOs and managing reliability through the use of…
Explore diffusion models for image generation, their physics-inspired foundations, and learn to train and deploy them on Vertex AI for state-of-the-art results.
Learn to query public tables and load sample data into BigQuery using the Web UI. Practice creating datasets, loading data, and running queries on custom and public datasets.
In this lab you will use a newly available ecommerce dataset to run some typical queries that businesses would want to know about their customers’ purchasing habits.
This challenge lab tests your skills and knowledge from the labs in the <b>Analyze BigQuery data in Connected Sheets<b> quest. You should be familiar with the content of labs before attempting this lab.
In this lab, you will create a series of visualizations from the Airports and Flights datasets and save them to a dashboard in Looker.
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