Dołącz Zaloguj się

Wykorzystuj swoje umiejętności w konsoli Google Cloud

Akshat Bindal

Jest członkiem od 2022

Liga srebrna

62995 pkt.
Odpowiedzialna AI dla deweloperów: obiektywność i uprzedzenia Earned lut 15, 2026 EST
Serverless Data Processing with Dataflow: Operations Earned gru 3, 2025 EST
Build Generative AI Agents with Vertex AI and Flutter Earned paź 12, 2025 EDT
Serverless Data Processing with Dataflow: Develop Pipelines Earned paź 4, 2025 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine Earned lip 29, 2025 EDT
Build intelligent agents with Agent Development Kit (ADK) Earned lip 26, 2025 EDT
Gen AI Agents: Transform Your Organization Earned maj 26, 2025 EDT
Gen AI Apps: Transform Your Work Earned maj 25, 2025 EDT
Gen AI: Navigate the Landscape Earned maj 25, 2025 EDT
Gen AI: Unlock Foundational Concepts Earned maj 21, 2025 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned maj 17, 2025 EDT
Explore Generative AI with the Gemini API in Vertex AI Earned maj 17, 2025 EDT
Gen AI: Beyond the Chatbot Earned maj 17, 2025 EDT
Tworzenie siatki danych przy użyciu Dataplex Earned maj 11, 2025 EDT
Build Real World AI Applications with Gemini and Imagen Earned kwi 27, 2025 EDT
Data Lake Modernization on Google Cloud: Cloud Composer Earned kwi 13, 2025 EDT
Create ML Models with BigQuery ML Earned mar 30, 2025 EDT
Boost Productivity with Gemini in BigQuery Earned mar 24, 2025 EDT
Using BigQuery Machine Learning for Inference Earned mar 24, 2025 EDT
Serverless Data Processing with Dataflow: Foundations Earned mar 21, 2025 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned mar 3, 2025 EST
Work with Gemini Models in BigQuery Earned mar 2, 2025 EST
Machine Learning Operations (MLOps) for Generative AI Earned mar 2, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned mar 2, 2025 EST
Working with Notebooks in Vertex AI Earned lut 22, 2025 EST
Build Streaming Data Pipelines on Google Cloud Earned lut 17, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Manage Features Earned lut 14, 2025 EST
Machine Learning Operations (MLOps): Getting Started Earned lut 14, 2025 EST
Uzyskiwanie statystyk z danych BigQuery Earned lut 1, 2025 EST
Professional Machine Learning Engineer Study Guide Earned sty 24, 2025 EST
Introduction to Data Engineering on Google Cloud Earned sty 24, 2025 EST
Build a Data Warehouse with BigQuery Earned sty 19, 2025 EST
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI Earned lis 27, 2024 EST
Prompt Design in Vertex AI Earned lis 23, 2024 EST
Build Batch Data Pipelines on Google Cloud Earned lis 23, 2024 EST
Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine Earned lis 17, 2024 EST
Gemini for end-to-end SDLC Earned lis 15, 2024 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned paź 1, 2024 EDT
Develop Gen AI Apps with Gemini and Streamlit Earned wrz 26, 2024 EDT
Preparing for your Professional Data Engineer Journey Earned wrz 22, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud - Polski Earned lip 12, 2024 EDT
Google Cloud Essentials Earned cze 3, 2024 EDT
Gemini for Data Scientists and Analysts Earned maj 29, 2024 EDT
Introduction to Responsible AI - Polski Earned maj 27, 2024 EDT
Introduction to Large Language Models - Polski Earned maj 26, 2024 EDT
Introduction to Generative AI - Polski Earned maj 26, 2024 EDT
Analyzing and Visualizing Data in Looker Earned maj 25, 2024 EDT
Introduction to Data Analytics on Google Cloud Earned maj 24, 2024 EDT
No Code November 2022 - Apps Scripts Earned lis 5, 2022 EDT

Na tym szkoleniu przedstawiamy koncepcje odpowiedzialnej AI i zasad dotyczących AI. Omawiamy praktyczne metody identyfikowania obiektywności i uprzedzeń, a także ograniczania występowania uprzedzeń podczas używania AI/ML. W trakcie szkolenia przedstawiamy też praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie odpowiedzialnej AI przy użyciu usług Google Cloud oraz narzędzi open source.

Więcej informacji

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.

Więcej informacji

In this course, you learn how to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.

Więcej informacji

In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.

Więcej informacji

In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine. Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.

Więcej informacji

This structured course is for developers interested in building intelligent agents using the Agent Development Kit (ADK). It combines hands-on experience, core concepts, and practical application, to provide a comprehensive guide to using ADK. You can also join our community of Google Cloud experts and peers to ask questions, collaborate on answers, and connect with the Googlers making the products you use every day.

Więcej informacji

Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.

Więcej informacji

Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

Więcej informacji

Gen AI: Navigate the Landscape s the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

Więcej informacji

Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.

Więcej informacji

Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini.

Więcej informacji

Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.

Więcej informacji

Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

Więcej informacji

Ukończ szkolenie wprowadzające Tworzenie siatki danych przy użyciu Dataplex, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: tworzenie siatki danych przy użyciu Dataplex w celu ułatwienia zarządzania danymi oraz ich wykrywania i ochrony w Google Cloud. Przećwiczysz i sprawdzisz swoje umiejętności w zakresie tagowania zasobów, przypisywania ról uprawnień i oceny jakości danych w Dataplex.

Więcej informacji

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 Vertex AI platform.

Więcej informacji

Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.

Więcej informacji

Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.

Więcej informacji

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.

Więcej informacji

Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.

Więcej informacji

This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.

Więcej informacji

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.

Więcej informacji

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.

Więcej informacji

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.

Więcej informacji

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.

Więcej informacji

This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.

Więcej informacji

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.

Więcej informacji

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. Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.

Więcej informacji

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.

Więcej informacji

Ukończ szkolenie wprowadzające Uzyskiwanie statystyk z danych BigQuery, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: pisanie zapytań SQL, tworzenie zapytań dotyczących tabel publicznych, wczytywanie przykładowych danych w BigQuery, naprawianie typowych błędów składniowych przy użyciu walidatora zapytań w BigQuery oraz tworzenie raportów w Looker Studio przez tworzenie połączenia z danymi BigQuery.

Więcej informacji

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.

Więcej informacji

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.

Więcej informacji

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.

Więcej informacji

Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.

Więcej informacji

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.

Więcej informacji

In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

Więcej informacji

Ukończ szkolenie wprowadzające Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: tworzenie i wdrażanie maszyn wirtualnych w Compute Engine oraz konfigurowanie sieciowych systemów równoważenia obciążenia i systemów równoważenia obciążenia aplikacji.

Więcej informacji

In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC). Duet AI was renamed to Gemini, our next-generation model.

Więcej informacji

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.

Więcej informacji

Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run.

Więcej informacji

This course helps learners create a study plan for the PDE (Professional Data 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.

Więcej informacji

Im szerzej wykorzystuje się w firmach sztuczną inteligencję i systemy uczące się, tym większej wagi nabiera odpowiedzialne podejście do opracowywania tych technologii. Wielu organizacjom trudniej jest jednak wprowadzić zasady odpowiedzialnej AI w praktyce niż tylko o tym rozmawiać. To szkolenie jest przeznaczone dla osób, które chcą się dowiedzieć, jak wdrożyć odpowiedzialną AI w swojej organizacji. W jego trakcie dowiesz się, jak robimy to w Google Cloud, oraz poznasz sprawdzone metody i wnioski z naszych działań w tym zakresie. Pomoże Ci to opracować własne podejście do odpowiedzialnej AI.

Więcej informacji

In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

Więcej informacji

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.

Więcej informacji

Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest odpowiedzialna AI i dlaczego jest ważna, oraz przedstawienie, jak Google wprowadza ją w swoich usługach. Szkolenie zawiera także wprowadzenie do siedmiu zasad Google dotyczących sztucznej inteligencji.

Więcej informacji

To szybkie szkolenie dla początkujących wyjaśnia, czym są duże modele językowe (LLM) oraz jakie są ich zastosowania. Przedstawia również możliwości zwiększenia ich wydajności przez dostrajanie przy użyciu promptów oraz narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.

Więcej informacji

Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest generatywna AI oraz jakie są jej zastosowania. Szkolenie przedstawia również różnice pomiędzy tą technologią a tradycyjnymi systemami uczącymi się, a także narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.

Więcej informacji

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

Więcej informacji

In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.

Więcej informacji

No-code development platforms allow programmers and non-programmers alike to build beautiful, useful apps. Complete labs to learn new skills and earn the badge. No experience needed!

Więcej informacji