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Purendeeswar Reddy

Member since 2025

Diamond League

14993 points
Deploy Gemini Enterprise with Workspace Data Sources and Model Armor Earned מאי 19, 2026 EDT
Introduction to AI and Machine Learning on Google Cloud Earned מאי 17, 2026 EDT
Baseline: Infrastructure Earned מאי 17, 2026 EDT
Data Migration Tool Earned מאי 13, 2026 EDT
Introduction to Data Engineering on Google Cloud Earned מאי 13, 2026 EDT
Implement Cloud Security Fundamentals on Google Cloud Earned מאי 11, 2026 EDT
Prepare Data for Looker Dashboards and Reports Earned מאי 11, 2026 EDT
Derive Insights from BigQuery Data Earned מאי 11, 2026 EDT
Improve Vertex AI Search and Gemini Enterprise Search Results Earned אפר 12, 2026 EDT
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service Earned אפר 10, 2026 EDT
Model evaluation on Vertex AI Earned אפר 9, 2026 EDT
Vertex AI Agent Builder Overview Earned מרץ 18, 2026 EDT
Implement RAG with Vertex AI Earned מרץ 18, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK) Earned פבר 19, 2026 EST
Build Agents with Agent Development Kit (ADK) Earned פבר 19, 2026 EST
Introduction to AI Agents Earned פבר 19, 2026 EST
Google Cloud: Prompt Engineering Guide Earned פבר 16, 2026 EST
Plan Change Management for Gemini Enterprise Deployments Earned ינו 24, 2026 EST
Agent Fundamentals Earned ינו 18, 2026 EST
AI Boost Bites: Poke Holes in Your Strategy Earned ינו 17, 2026 EST
AI Boost Bites: NotebookLM for Competitive Edge Earned ינו 17, 2026 EST
AI Boost Bites: Personalization with customized prompts Earned ינו 17, 2026 EST
AI Boost Bites: TL;DR with Gemini in Docs & Drive Earned ינו 17, 2026 EST
AI Boost Bites: Prompting like a Pro with Google Workspace Earned ינו 17, 2026 EST
Vertex AI Search for Commerce Earned ספט 5, 2025 EDT
Work with Gemini Models in BigQuery Earned אוג 26, 2025 EDT
Create Embeddings, Vector Search, and RAG with BigQuery Earned אוג 26, 2025 EDT
Boost Productivity with Gemini in BigQuery Earned אוג 10, 2025 EDT
Text Prompt Engineering Techniques Earned אוג 8, 2025 EDT
Introduction to Generative AI Studio - בעברית Earned אוג 6, 2025 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned אוג 4, 2025 EDT
Generative AI for Business Leaders Earned אוג 1, 2025 EDT
Generative AI Fundamentals Earned יול 31, 2025 EDT
Introduction to Responsible AI - בעברית Earned יול 31, 2025 EDT

In this challenge lab, you act as a Security Engineer deploying a secure Gemini Enterprise environment for Cymbal Bank. You will ground Gemini in web search and internal Workspace sources to ensure accurate, contextual responses. To maintain compliance, you will configure Model Armor policies to filter sensitive data and block threats like prompt injections and malicious URLs. Finally, you will manage specific end-user features to customize the AI experience safely

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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.

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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with migrating from an Enterprise Data Warehouse (EDW) to BigQuery using the DMT tool and sample data. Learners will complete a lab that uses the DMT tool to transfer schema and data from Teradata to BigQuery.

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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.

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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.

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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.

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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 Data Studio by connecting to BigQuery data.

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If you've worked with data, you know that some data is more reliable than other data. In this course, you'll learn a variety of techniques to present the most reliable or useful results to your users. Create serving controls to boost or bury search results. Rank search results to ensure that each query is answered by the most relevant data. If needed, tune your search engine. Learn to measure search results to ensure your search applications deliver the best possible results to each user. (Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)

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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.

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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.

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In this course, you will learn about Vertex AI Agent Builder and determine the need for it. You will focus on the opportunity around Generative Artificial Intelligence (Gen AI) agents. You will learn what an agent is and how it helps customers transform businesses. You will identify the key challenges in operationalizing and productionizing agents. You will also learn about the value proposition of Vertex AI Agent Builder, how to identify the right customer use cases, and review the guidelines for selling the application.

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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.

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Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK). In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code.

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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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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.

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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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This course will guide you through designing customer engagements that result in successful, well-utilized Gemini Enterprise deployments. Study the art of change management, how to identify and engage sponsors, recruit early adopters, help your customer identify and address cultural change challenges and skills gaps, and effectively deliver project communications. Additionally, learn how to support your customer to plan, offer, conduct, and evaluate end-user training, leverage partner resources, and create essential project documents.

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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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AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.

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This video will cover how to use NotebookLM to gather and analyze publicly available information, combine it with internal documents, and extract key competitive insights.

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This video covers how to personalize your Gemini results in Google Workspace. Learn to incorporate documents and research papers directly into your prompts using the "@" symbol to get more targeted and relevant AI output tailored to your needs.

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This video covers how you can use Gemini to summarize long documents in Google Workspace, so you can quickly get the information you need and save time. You'll learn how to use Gemini to summarize entire documents or just selected text, as well as how to use Gemini in Drive to summarize across multiple files.

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This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.

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This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.

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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.

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This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.

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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.

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בקורס הזה נלמד על Generative AI Studio, מוצר ב-Vertex AI שעוזר ליצור אבות טיפוס למודלים של בינה מלאכותית גנרטיבית, כדי להשתמש בהם ולהתאים אותם לפי הצרכים שלכם. באמצעות הדגמה של המוצר עצמו, נלמד מהו Generative AI Studio, מהם הפיצ'רים והאפשרויות שלו, ואיך להשתמש בו. בסוף הקורס יהיה שיעור Lab מעשי לתרגול של מה שנלמד, ובוחן לבדיקת הידע.

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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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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.

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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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זהו קורס מבוא ממוקד שמטרתו להסביר מהי אתיקה של בינה מלאכותית, למה היא חשובה ואיך Google נוהגת לפי כללי האתיקה של הבינה המלאכותית במוצרים שלה. מוצגים בו גם 7 עקרונות ה-AI של Google.

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