Stanislav Nabatnikov
Member since 2023
Diamond League
65910 points
Deploy Your First Agent
Earned авг. 21, 2026 EDT
Build and Deploy Agents in Production
Earned авг. 20, 2026 EDT
Add Agent Capabilities With Tools
Earned авг. 3, 2026 EDT
Manage Agent Memory and State
Earned авг. 2, 2026 EDT
Optimize Agent Behavior
Earned авг. 2, 2026 EDT
Engineer AI Agents with Agent Development Kit (ADK)
Earned июля 30, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned июля 30, 2026 EDT
Create Your First Gemini Enterprise Application
Earned июля 30, 2026 EDT
Enterprise Agents and Use Cases
Earned июля 30, 2026 EDT
Agent Fundamentals
Earned июля 30, 2026 EDT
Build Real World AI Applications with Gemini and Imagen
Earned окт. 27, 2025 EDT
Prompt Design in Agent Platform
Earned окт. 26, 2025 EDT
Set Up a Google Cloud Network
Earned окт. 21, 2025 EDT
Build Streaming Data Pipelines on Google Cloud
Earned дек. 3, 2023 EST
Build a Certification Study Guide: PDE Exam Prep
Earned дек. 3, 2023 EST
Baseline: Infrastructure
Earned нояб. 10, 2023 EST
Data Catalog Fundamentals
Earned нояб. 10, 2023 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned нояб. 9, 2023 EST
Build a Data Warehouse with BigQuery
Earned окт. 31, 2023 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned окт. 30, 2023 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned окт. 28, 2023 EDT
Develop Your Google Cloud Network
Earned окт. 28, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned окт. 28, 2023 EDT
Configure Service Accounts and IAM Roles for Google Cloud
Earned окт. 24, 2023 EDT
Monitoring in Google Cloud
Earned окт. 18, 2023 EDT
Elastic on Google Cloud
Earned окт. 18, 2023 EDT
The Basics of Google Cloud Compute
Earned окт. 16, 2023 EDT
Create a Streaming Data Lake on Cloud Storage
Earned окт. 14, 2023 EDT
Automate Data Capture at Scale with Document AI
Earned окт. 13, 2023 EDT
Analyze Images with the Cloud Vision API
Earned окт. 12, 2023 EDT
Deploy and Secure Serverless APIs with API Gateway
Earned окт. 11, 2023 EDT
Prepare Data for ML APIs on Google Cloud
Earned окт. 11, 2023 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned окт. 10, 2023 EDT
Analyze BigQuery Data in Connected Sheets
Earned окт. 10, 2023 EDT
Implement Event-Driven Messaging and Automation Workflows
Earned окт. 10, 2023 EDT
Exploring and Preparing your Data with BigQuery
Earned окт. 10, 2023 EDT
Deploy Kubernetes Applications on Google Cloud
Earned окт. 10, 2023 EDT
Deploy and Manage Applications on Google App Engine
Earned окт. 9, 2023 EDT
Build Serverless Applications with Cloud Run Functions
Earned окт. 9, 2023 EDT
Monitor and Manage Google Cloud Resources
Earned окт. 9, 2023 EDT
App Building with AppSheet
Earned окт. 8, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Console
Earned окт. 8, 2023 EDT
Use Functions, Formulas, and Charts in Google Sheets
Earned окт. 8, 2023 EDT
Implement Cloud Collaboration and Productivity Workflows
Earned окт. 7, 2023 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned окт. 6, 2023 EDT
Encoder-Decoder Architecture
Earned окт. 5, 2023 EDT
[DEPRECATED]Introduction to Responsible AI
Earned окт. 5, 2023 EDT
Secure Lakehouse Data
Earned окт. 4, 2023 EDT
Enrich Metadata and Discovery of Lakehouse Data
Earned окт. 4, 2023 EDT
Implement Cloud Storage and Data Protection Solutions
Earned окт. 4, 2023 EDT
Use APIs to Work with Cloud Storage
Earned окт. 3, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Command Line
Earned окт. 3, 2023 EDT
Organize and Govern Data with Knowledge Catalog
Earned окт. 3, 2023 EDT
Manage Data Models in Looker
Earned окт. 3, 2023 EDT
Understanding LookML in Looker
Earned окт. 2, 2023 EDT
Build LookML Objects in Looker
Earned сент. 29, 2023 EDT
Prepare Data for Looker Dashboards and Reports
Earned сент. 28, 2023 EDT
Create and Manage Bigtable Instances
Earned сент. 27, 2023 EDT
Set Up an App Dev Environment on Google Cloud
Earned сент. 25, 2023 EDT
Share Data Using Google Data Cloud
Earned сент. 24, 2023 EDT
Perform Predictive Data Analysis in BigQuery
Earned сент. 24, 2023 EDT
[Deprecated] Get Started with Looker
Earned сент. 23, 2023 EDT
Derive Insights from BigQuery Data
Earned сент. 23, 2023 EDT
Generative AI Fundamentals
Earned сент. 22, 2023 EDT
Introduction to Large Language Models
Earned сент. 22, 2023 EDT
Introduction to Generative AI
Earned сент. 22, 2023 EDT
Create and Manage AlloyDB Instances
Earned сент. 22, 2023 EDT
Google Cloud Data Analytics Essentials
Earned сент. 21, 2023 EDT
Take your agents from localhost to production. This course teaches you to deploy ADK agents to Agent Runtime and Cloud Run, with optional cross-session memory via Memory Bank.
Explore other content in the Gemini Agent Ready (GEAR) program.
Join the community forum for questions and discussions
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Explore the architecture and deployment of multi-agent systems using Google’s Agent Development Kit (ADK) and Google Cloud’s robust infrastructure. You will learn to design hierarchical agent trees and deterministic workflow agents while identifying the ideal hosting environment—from serverless Cloud Run to high-performance GKE—to ensure your AI agents are secure, scalable, and production-ready. Explore other content in the Gemini Agent Ready (GEAR) program.
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You’ve built agents with advanced configuration—now give them real-world capabilities. Equip agents with tools that enable searching the web, executing code, querying databases, and performing custom actions. Transform agents from intelligent responders into capable assistants that take action.
Explore other content in the Gemini Agent Ready (GEAR) program.
Join the community forum for questions and discussions
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You've built basic LLM agents that respond to queries—now let's make them stateful. Use session state to build agents that maintain context, remember user preferences, and provide personalized experiences. Transform agents from stateless responders to intelligent assistants.
Explore other content in the Gemini Agent Ready (GEAR) program.
Join the community forum for questions and discussions
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You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns.
Explore other content in the Gemini Agent Ready (GEAR) program.
Join the community forum for questions and discussions
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Complete the intermediate Engineer AI Agents with Agent Development Kit (ADK) skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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 Gemini platform.
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
Explore other content in the Gemini Agent Ready (GEAR) program.
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Create your first Gemini Enterprise application to earn a skill badge! Connect diverse data sources to your application to build a powerful, unified search and analysis engine. Master advanced capabilities like deep research agents, multi-agent ideation, and Gemini Notebook for focused analysis. Explore other content in the Gemini Agent Ready (GEAR) program.
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Discover how AI agents drive business impact. You’ll map agent types to your KPIs and explore use cases that solve real bottlenecks. Then, learn how Gemini Enterprise empowers you to build and orchestrate the right agents—from no-code to high-code solutions. Explore other content in the Gemini Agent Ready (GEAR) program.
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This course introduces the fundamentals of AI agents and explores where agents add value in the real world. It provides a foundation for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior.
Explore other content in the Gemini Agent Ready (GEAR) program.
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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Google Cloud Agent Platform. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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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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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
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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.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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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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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.
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Earn the Introductory skill badge by completing the Configure Service Accounts and IAM Roles for Google Cloud course, where you learn about service accounts, custom roles, and how to set permissions using gcloud .
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Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.
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In this game you will create a simple Elasticsearch deployment, use Elastic Stack to monitor Google Cloud, import synthetic data representing financial records offloaded from a bank's mainframe into BigQuery, and gain hands-on experience with Generative AI on Google Cloud.
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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
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Earn a skill badge by completing the Create a Streaming Data Lake on Cloud Storage course, where you use Pub/Sub, Dataflow, and Cloud Storage together to create a streaming data lake on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.
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Earn a skill badge by completing the Deploy and Secure Serverless APIs with API Gateway skill badge course, where you learn how to use API Gateway to deploy, secure, and manage APIs with a fully managed gateway.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.
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Complete the Analyze BigQuery Data in Connected Sheets skill badge to demonstrate that you can use Connected Sheets to access, analyze, visualize, and share billions of rows of BigQuery data from your Google Sheets spreadsheet.
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Earn a skill badge by completing the Implement Event-Driven Messaging and Automation Workflows skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.
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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets.
This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
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Earn a Skill Badge by completing the Deploy and Manage Applications on Google App Engine course, where you learn how to use App Engine with Python, Go, and PHP.
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Earn a Introductory skill badge by completing the Build Serverless Applications with Cloud Run Functions course, where you learn how to use Cloud Run functions through the Google Cloud console and on the command line.
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Complete the introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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Earn a skill badge by completing the App Building with AppSheet course, where you learn how to build, configure, and publish apps using AppSheet.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Complete the intermediate Use Functions, Formulas and Charts in Google Sheets skill badge course to demonstrate skills in the following: analyzing data with functions; visualizing data using charts; and searching, validating, formatting, and displaying data.
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Earn an introductory skill badge by completing the Implement Cloud Collaboration and Productivity Workflows course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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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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Complete the introductory Secure Lakehouse Data skill badge course to demonstrate skills with IAM, BigQuery, Lakehouse, and Knowledge Catalog to create and secure Lakehouse tables.
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Complete the Enrich Metadata and Discovery of Lakehouse Data skill badge course to demonstrate skills in BigQuery, Lakehouse, and Knowledge Catalog. You create Lakehouse tables and enrich metadata management and discovery of the table data.
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Earn a Skill Badge by completing the Implement Cloud Storage and Data Protection Solutions course. Learn to create a Cloud Storage bucket, use the command line, and protect objects with Bucket Lock.
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Complete the introductory Use APIs to Work with Cloud Storage skill badge to demonstrate skills in the following: using APIs to work with Cloud Storage resources, including the Cloud Storage API.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Complete the introductory Organize and Govern Data with Knowledge Catalog skill badge to demonstrate skills in the following: creating Knowledge Catalog assets, creating aspect types, and applying aspects to entries in Knowledge Catalog.
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Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.
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In this course, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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Complete the introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.
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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 Create and Manage Bigtable Instances skill badge to demonstrate skills in the following: creating instances, designing schemas, querying data, and performing administrative tasks in Bigtable including monitoring performance and configuring node autoscaling and replication.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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Earn a skill badge by completing the Share Data Using Google Data Cloud skill badge course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards.
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Complete the intermediate Perform Predictive Data Analysis in BigQuery skill badge course to demonstrate skills in the following: creating datasets in BigQuery by importing CSV and JSON files; harnessing the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on soccer event data and evaluate the impressiveness of World Cup goals.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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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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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. 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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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. Explore other content in the Gemini Agent Ready (GEAR) program.
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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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Complete the introductory Create and Manage AlloyDB Instances skill badge to demonstrate skills in the following: performing core AlloyDB operations and tasks, migrating to AlloyDB from PostgreSQL, administering an AlloyDB database, and accelerating analytical queries using the AlloyDB Columnar Engine.
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Discover how to turn raw numbers into clear, data-driven decisions on Google Cloud. Through hands-on labs and practical real-world scenarios, this beginner-level course guides you through querying data in BigQuery, exploring trends in Looker, and crafting shareable, interactive reports in Data Studio.
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