Xin Yi Lim
Учасник із 2025
Діамантова ліга
Кількість балів: 7827
Agent Fundamentals
Earned черв. 19, 2026 EDT
Introduction to AI Agents
Earned черв. 19, 2026 EDT
Skills Boost Arcade Trivia October 2025 Week 1
Earned жовт. 16, 2025 EDT
Create Generative AI Apps on Google Cloud
Earned вер. 23, 2025 EDT
Google Developer Essentials
Earned вер. 20, 2025 EDT
Vertex AI Search for Commerce
Earned вер. 20, 2025 EDT
Work with Gemini Models in BigQuery
Earned вер. 20, 2025 EDT
Automate Data Capture at Scale with Document AI
Earned вер. 20, 2025 EDT
Implement Speech and Language Solutions with Pre-trained APIs
Earned вер. 19, 2025 EDT
Build Google Cloud Infrastructure for AWS Professionals
Earned вер. 19, 2025 EDT
[Depricated] Build, Train and Deploy ML Models with Keras on Google Cloud
Earned вер. 18, 2025 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud
Earned вер. 18, 2025 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned вер. 16, 2025 EDT
Create ML Models with BigQuery ML
Earned вер. 16, 2025 EDT
Introduction to Generative AI - Українська
Earned вер. 13, 2025 EDT
[DEPRECATED] Feature Engineering
Earned вер. 11, 2025 EDT
Use Machine Learning APIs on Google Cloud
Earned вер. 11, 2025 EDT
Build a Certification Study Guide: PMLE
Earned вер. 11, 2025 EDT
Prompt Design in Agent Platform
Earned вер. 10, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned лип. 10, 2025 EDT
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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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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Hey there! You're invited to game on with Skills Boost Arcade Trivia for October Week 1! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the October Trivia Week 1 badge!
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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud?
In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application. Explore other content in the Gemini Agent Ready (GEAR) program.
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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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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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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 the Introductory Skill Badge by completing the Implement Speech and Language Solutions with Pre-trained APIs course, where you learn how to use speech related API tools to synthesise and transcribe speech.
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Earn a skill badge by completing the Build Google Cloud Infrastructure for AWS Professionals course, where you learn how to configure IAM permission, orchestrate workloads using Kubernetes, host a web application using compute engine, and configure load balancing.
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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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Пройдіть вступний кваліфікаційний курс Підготовка даних для інтерфейсів API машинного навчання в Google Cloud, щоб продемонструвати свої навички щодо очистки даних за допомогою сервісу Dataprep by Trifacta, запуску конвеєрів даних у Dataflow, створення кластерів і запуску завдань Apache Spark у Managed Service for Apache Spark, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API.
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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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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.
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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке генеративний штучний інтелект, як він використовується й чим відрізняється від традиційних методів машинного навчання. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучногоінтелекту.
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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
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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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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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