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Yassine Rakibi

Member since 2024

Diamond League

45669 points
Generative AI for Document Processing Earned Oct 31, 2025 EDT
Boost Productivity with Gemini in BigQuery Earned Oct 10, 2025 EDT
Streaming Analytics into BigQuery Earned Nov 6, 2024 EST
Automate Data Migrations to BigQuery Earned Nov 6, 2024 EST
Monitor and Manage Data in BigQuery Earned Oct 31, 2024 EDT
Perform Predictive Data Analysis in BigQuery Earned Oct 29, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned Oct 28, 2024 EDT
Create ML Models with BigQuery ML Earned Oct 25, 2024 EDT
Build a Data Warehouse with BigQuery Earned Oct 24, 2024 EDT
Create a Secure Data Lake on Cloud Storage Earned Oct 22, 2024 EDT
Tag and Discover BigLake Data Earned Oct 22, 2024 EDT
Prepare Data for ML APIs on Google Cloud Earned Oct 21, 2024 EDT
Derive Insights from BigQuery Data Earned Oct 21, 2024 EDT
Create Image Captioning Models Earned Oct 18, 2024 EDT
Introduction to Image Generation Earned Oct 18, 2024 EDT
Security & Identity Fundamentals Earned Oct 18, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud Earned Oct 15, 2024 EDT
Scaling with Google Cloud Operations Earned Oct 15, 2024 EDT
Trust and Security with Google Cloud Earned Oct 15, 2024 EDT
Modernize Infrastructure and Applications with Google Cloud Earned Oct 15, 2024 EDT
Innovating with Google Cloud Artificial Intelligence Earned Oct 7, 2024 EDT
Exploring Data Transformation with Google Cloud Earned Oct 7, 2024 EDT
Digital Transformation with Google Cloud Earned Oct 7, 2024 EDT
Transformer Models and BERT Model Earned Oct 3, 2024 EDT
Encoder-Decoder Architecture Earned Oct 2, 2024 EDT
Text Prompt Engineering Techniques Earned Oct 1, 2024 EDT
Generative AI Fundamentals Earned Oct 1, 2024 EDT
Introduction to Vertex AI Studio Earned Sep 30, 2024 EDT
Data Lake Modernization on Google Cloud Earned Sep 30, 2024 EDT
Data Catalog Fundamentals Earned Sep 27, 2024 EDT
Get Started with Sensitive Data Protection Earned Sep 24, 2024 EDT
Secure BigLake Data Earned Sep 23, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned Sep 21, 2024 EDT
Introduction to Responsible AI Earned Sep 20, 2024 EDT
Generative AI for Business Leaders Earned Sep 20, 2024 EDT
Build a Data Mesh with Dataplex Earned Sep 19, 2024 EDT
Get Started with Dataplex Earned Sep 12, 2024 EDT
Attention Mechanism Earned Sep 9, 2024 EDT

Explore how to use AI to automate document processing tasks, such as classifying documents, extracting data from documents, and summarizing documents. Learn how to use the Document AI Workbench to create custom document extractors and summarizers. Upload documents, define fields, create versions, and call endpoints to get structured data and summaries back. Discover a new service called Document AI Warehouse, which is a fully managed service to search, store, govern, and manage documents and their extracted metadata. You will also learn about how it integrates with other Google Cloud services like Document AI, BigQuery, and Cloud Storage.

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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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Earn a skill badge by completing the Streaming Analytics into BigQuery skill badge course, where you use Pub/Sub, Dataflow and BigQuery together to stream data for analytics.

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This skill badge aims to provide partners an introduction to BigQuery Data Transfer Service and Migration Service, two powerful tools for managing and migrating data in the cloud. Learners will learn how to leverage these tools to efficiently migrate and manage data, and gain hands-on experience through labs.

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This skill badge aims to evaluate a partner's ability to utilize BigQuery's features and capabilities to manage and analyze large datasets. Learners will gain hands-on experience through labs and achieve solid understanding of BigQuery's foundational concepts and features.

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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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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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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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Complete the introductory Create a Secure Data Lake on Cloud Storage skill badge course to demonstrate skills in the following: securing and configuring a Cloud Storage bucket, using Gemini for text generation, managing IAM access control, and establishing a Dataplex lake for data governance.

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Earn a skill badge by completing the Tag and Discover BigLake Data skill badge course, where you use BigQuery, BigLake, and Data Catalog within Dataplex to create, tag, and discover BigLake tables.

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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 Dataproc, 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 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 Looker Studio by connecting to BigQuery data.

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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images

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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.

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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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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.

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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.

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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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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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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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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.

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This course focuses on how you can bring your on-premises data lakes and workloads to Google Cloud to unlock cost savings and scale.

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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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Complete the introductory Get Started with Sensitive Data Protection skill badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.

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Complete the introductory Secure BigLake Data skill badge course to demonstrate skills with IAM, BigQuery, BigLake, and Dataplex to create and secure BigLake tables.

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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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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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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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Complete the introductory Build a Data Mesh with Dataplex skill badge to demonstrate skills in the following: building a data mesh with Dataplex to facilitate data security, governance, and discovery on Google Cloud. You practice and test your skills in tagging assets, assigning IAM roles, and assessing data quality in Dataplex.

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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.

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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.

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