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Alisha Rath

Member since 2016

Gold League

2815 points
Gemini for Data Scientists and Analysts Earned апр. 16, 2026 EDT
Deploy Your First Agent Earned апр. 12, 2026 EDT
Build Agents with Agent Development Kit (ADK) Earned апр. 11, 2026 EDT
Orchestrate Complex Multi-Agent Workflows Earned апр. 9, 2026 EDT
Coordinate Multiple Agents Earned апр. 9, 2026 EDT
Agent Fundamentals Earned апр. 6, 2026 EDT
Prompt Design in Vertex AI Earned апр. 6, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned марта 30, 2026 EDT
Introduction to Responsible AI Earned марта 28, 2026 EDT
Introduction to Large Language Models Earned марта 27, 2026 EDT
Introduction to Generative AI Earned марта 27, 2026 EDT

In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows. Duet AI was renamed to Gemini, our next-generation model.

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Take your agents from localhost to production. This course teaches you to deploy ADK agents to Vertex AI Agent Engine and Cloud Run, with optional cross-session memory via Memory Bank.

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Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems.

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Learn to orchestrate complex multi-agent workflows. This lesson teaches you to choose the right workflow patterns, manage state across agents, understand when custom logic is needed, and introduces distributed agent systems with A2A Protocol.

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Learn to coordinate multiple specialized agents working together. This lesson teaches you when to use multi-agent systems, how to orchestrate agents with workflow patterns, and how agents communicate through shared state. By the end, you’ll build a complete multi-agent application.

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AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.

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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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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.

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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.

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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.

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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.

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