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Olaya Folgueiras González

Jest członkiem od 2023

Liga diamentowa

23606 pkt.
Engineer Data for Predictive Modeling with BigQuery ML Earned lip 16, 2025 EDT
Create ML Models with BigQuery ML Earned lip 14, 2025 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud Earned lip 10, 2025 EDT
Working with Notebooks in Vertex AI Earned lip 9, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud Earned gru 27, 2024 EST
Feature Engineering Earned lut 14, 2024 EST
Build, Train and Deploy ML Models with Keras on Google Cloud Earned lut 2, 2024 EST
Machine Learning in the Enterprise Earned sty 30, 2024 EST
Applying Machine Learning to your Data with Google Cloud Earned sty 23, 2024 EST
Achieving Advanced Insights with BigQuery Earned sty 22, 2024 EST
Creating New BigQuery Datasets and Visualizing Insights Earned sty 15, 2024 EST
Exploring and Preparing your Data with BigQuery Earned sty 5, 2024 EST
Google Cloud Fundamentals: Core Infrastructure - Polski Earned gru 21, 2023 EST

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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Ukończ szkolenie wprowadzające Przygotowywanie danych do użycia z interfejsami ML w Google Cloud, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: czyszczenie danych przy użyciu usługi Dataprep firmy Trifacta, uruchamianie potoków danych w Dataflow, tworzenie klastrów i uruchamianie zadań Apache Spark w Dataproc, a także wywoływanie interfejsów API dotyczących uczenia maszynowego, w tym Cloud Natural Language API, Google Cloud Speech-to-Text API oraz Video Intelligence API. Odznaka umiejętności to wyjątkowa cyfrowa odznaka wydawana przez Google Cloud, która potwierdza Twoją wiedzę o produktach i usługach Google Cloud. Aby ją zdobyć, musisz pokazać, że potrafisz zastosować zdobytą wiedzę w praktycznym, interaktywnym środowisku. Ukończ to szkolenie oraz moduł Challenge Lab, aby zdobyć odznakę umiejętności, którą możesz udostępnić w swojej sieci kontaktów.

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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.

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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.

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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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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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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.

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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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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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Szkolenie Google Cloud Fundamentals: Core Infrastructure wprowadza ważne pojęcia i terminologię potrzebne w pracy z Google Cloud. Za pomocą filmów i praktycznych modułów szkolenie prezentuje oraz porównuje usługi Google Cloud umożliwiające między innymi przetwarzanie i przechowywanie danych, a także zawiera ważne materiały i narzędzia do zarządzania zasadami.

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