Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.
En savoir plus
Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.
En savoir plus
This course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications.
En savoir plus
Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.
En savoir plus
This course introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of Google Cloud products and open-source tools.
En savoir plus
This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
En savoir plus
This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
En savoir plus
This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production.
Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
En savoir plus
This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
En savoir plus
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
En savoir plus
This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
En savoir plus
As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Virtual Agent self-service experiences.
En savoir plus
In this course, you will learn the important role that different types of webhooks play in Dialogflow CX development, and how to effectively integrate them into your routine configuration of a Virtual Agent.
Derive Insights from BigQuery Data
Earned août 15, 2025 EDT
Get Started with Dataplex
Earned août 11, 2025 EDT
Model Armor: Securing AI Deployments
Earned août 10, 2025 EDT
Introduction to Security in the World of AI
Earned août 10, 2025 EDT
Responsible AI for Developers: Privacy & Safety
Earned août 10, 2025 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned août 10, 2025 EDT
Responsible AI for Developers: Fairness & Bias
Earned août 10, 2025 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned août 4, 2025 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned août 4, 2025 EDT
Machine Learning Operations (MLOps): Getting Started
Earned août 4, 2025 EDT
Professional Machine Learning Engineer Study Guide
Earned août 4, 2025 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned juil. 18, 2025 EDT
Introduction to Responsible AI
Earned juil. 18, 2025 EDT
Introduction to Large Language Models
Earned juil. 18, 2025 EDT
Introduction to Generative AI
Earned juil. 18, 2025 EDT
[Deprecated] Advanced Webhook Concepts
Earned juil. 15, 2025 EDT
[DEPRECATED] Webhook fundamentals
Earned juil. 15, 2025 EDT