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Thalita Sanchez Castro

Date d'abonnement : 2022

Gen AI Apps: Transform Your Work Earned jan. 27, 2026 EST
Gen AI Agents: Transform Your Organization Earned jan. 26, 2026 EST
Gen AI: Navigate the Landscape Earned nov. 29, 2025 EST
Gen AI: Unlock Foundational Concepts Earned nov. 14, 2025 EST
Gen AI: Beyond the Chatbot Earned nov. 7, 2025 EST
Cloud Hero: Scalable ML Earned juil. 25, 2024 EDT
Generative AI Explorer Earned juin 18, 2024 EDT
Generative AI and ML with Vertex AI Earned mai 28, 2024 EDT
Vertex AI Earned avr. 23, 2024 EDT
ML API Skills Earned mars 26, 2024 EDT
Serverless Data Processing with Dataflow: Foundations Earned mars 19, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud Earned fév. 22, 2024 EST
Build Streaming Data Pipelines on Google Cloud Earned fév. 20, 2024 EST
Build Batch Data Pipelines on Google Cloud Earned nov. 9, 2023 EST
Cloud Hero Data Skills Earned nov. 1, 2023 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned sept. 22, 2023 EDT
Cloud Hero BQML Earned sept. 21, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned sept. 19, 2023 EDT

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 Gemini Notebook. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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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. Explore other content in the Gemini Agent Ready (GEAR) program.

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Gen AI: Navigate the Landscape is 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.

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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.

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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.

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Machine Learning is essential to many modern applications nowadays. At the same time, expectations towards ML capabilities and thus complexity & size of ML models and datasets grows rapidly. In this game, you’ll experiment hands-on with how to scale ML “like Google” to iterate quickly on complex ML challenges and take your ML tasks to the next level.

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Welcome Gamers! Create and test a prompt, create a conversation, and explore the prompt gallery, all while having fun! Explore Generative AI Studio in Vertex AI. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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Welcome Gamers! Train a model on your own image dataset, while having fun! Build, run, and get metadata for an end-to-end ML pipeline on Vertex Pipelines. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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Welcome Gamers! Learn Google Cloud's Vertex AI, all while having fun! Vertex AI is Google Cloud's unified ML platform for solving your tough business problems. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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Welcome Gamers! Explore the power of machine learning by using multiple machine learning APIs together, all while having fun! Translate the text with the Translation API and analyze it with the Natural Language API. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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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.

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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

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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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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.

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Welcome Gamers! Learn Google Cloud Dataprep, create a streaming pipeline using a Google-Provided Cloud Dataflow template, work with gcloud Command Line, all while having fun! Extract entities from a snippit of text using the Cloud Natural Language API You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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Welcome Gamers! Learn the fundamentals of BQML, all while having fun! In this game, you will learn to use the python-based command line tool for BigQuery. The hands-on labs will help you create a machine learning model, a classification model, and a forecasting model. Earn the points by completing the steps in the lab... Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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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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