Dipika Patil

Date d'abonnement : 2025

Ligue d'Or

4098 points

Introduction to Responsible AI Earned nov. 15, 2025 EST

Introduction to Large Language Models Earned nov. 15, 2025 EST

Introduction to Generative AI Earned nov. 15, 2025 EST

Build a Certification Study Guide: PMLE Earned nov. 14, 2025 EST

Build Data Lakes and Data Warehouses on Google Cloud Earned nov. 4, 2025 EST

Introduction to Data Engineering on Google Cloud Earned oct. 31, 2025 EDT

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 3 AI principles.

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.

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.

Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.

While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.