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Markus Baersch

Jest członkiem od 2020

Liga srebrna

6900 pkt.
Odznaka dla Data Science on Google Cloud Data Science on Google Cloud Earned gru 29, 2022 EST
Odznaka dla DEPRECATED Explore Machine Learning Models with Explainable AI DEPRECATED Explore Machine Learning Models with Explainable AI Earned paź 19, 2020 EDT
Odznaka dla [DEPRECATED] Data Engineering [DEPRECATED] Data Engineering Earned paź 16, 2020 EDT
Odznaka dla Build a Website on Google Cloud Build a Website on Google Cloud Earned paź 16, 2020 EDT
Odznaka dla Data Science on Google Cloud: Machine Learning Data Science on Google Cloud: Machine Learning Earned paź 13, 2020 EDT
Odznaka dla Scientific Data Processing Scientific Data Processing Earned paź 10, 2020 EDT
Odznaka dla Machine Learning APIs Machine Learning APIs Earned paź 8, 2020 EDT
Odznaka dla Intro to ML: Image Processing Intro to ML: Image Processing Earned paź 7, 2020 EDT
Odznaka dla Intro to ML: Language Processing Intro to ML: Language Processing Earned paź 7, 2020 EDT
Odznaka dla Baseline: Data, ML, AI Baseline: Data, ML, AI Earned paź 7, 2020 EDT
Odznaka dla Google Developer Essentials Google Developer Essentials Earned paź 7, 2020 EDT
Odznaka dla Workspace: Add-ons Workspace: Add-ons Earned paź 6, 2020 EDT
Odznaka dla Website on Google Cloud Website on Google Cloud Earned paź 4, 2020 EDT
Odznaka dla Exploring APIs Exploring APIs Earned paź 4, 2020 EDT
Odznaka dla BigQuery for Machine Learning BigQuery for Machine Learning Earned paź 3, 2020 EDT
Odznaka dla BigQuery for Data Warehousing BigQuery for Data Warehousing Earned paź 2, 2020 EDT
Odznaka dla Data Catalog Fundamentals Data Catalog Fundamentals Earned paź 2, 2020 EDT
Odznaka dla BigQuery for Marketing Analysts BigQuery for Marketing Analysts Earned paź 2, 2020 EDT
Odznaka dla DEPRECATED BigQuery for Data Analysis DEPRECATED BigQuery for Data Analysis Earned paź 1, 2020 EDT
Odznaka dla Getting Started - Create and Manage Cloud Resource Getting Started - Create and Manage Cloud Resource Earned paź 1, 2020 EDT
Odznaka dla Google Cloud Essentials Google Cloud Essentials Earned paź 1, 2020 EDT
Odznaka dla Insights from Data with BigQuery Insights from Data with BigQuery Earned wrz 30, 2020 EDT
Odznaka dla BigQuery Basics for Data Analysts BigQuery Basics for Data Analysts Earned wrz 30, 2020 EDT

This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.

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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest and the final assessment challenge lab to receive a skill badge that you can share with your network.

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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.

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W ramach tego kursu poznasz 4 dostępne architektury stron Google Cloud, dzięki czemu Twoja strona będzie dostępna i skalowalna. Jeśli ukończysz ten kurs wraz z Challenge Lab na końcu, otrzymasz cyfrową plakietkę Google Cloud. Challenge Lab nie zawiera dokładnych instrukcji – wymaga opracowania rozwiązań z minimalną pomocą, przez co sprawdza umiejętności użytkownika w zakresie technologii Google Cloud. Ten kurs jest oparty na serii materiałów wideo Get Cooking in Cloud.

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This is the second of two Quests of hands-on labs derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.

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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.

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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level quest, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.

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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.

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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and AI Platform. Want extra help? 1-minute videos walk you through key concepts for each lab.

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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 quest of hands-on labs demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.

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In this quest you will learn about the four Google Cloud website architectures available to ensure that your website is available and scalable. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional challenge lab at the end of this Build a Website on Google Cloud to receive an exclusive Google Cloud digital badge. This quest is based on the video series Get Cooking in Cloud.

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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.

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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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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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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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Want to learn the core SQL and visualization skills of a Data Analyst? Interested in how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.

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W tym kursie z poziomu wprowadzającego możesz przećwiczyć korzystanie z podstawowych narzędzi i usług Google Cloud. Pierwsze kroki – Tworzenie zasobów w Google Cloud i zarządzanie nimi to pierwszy kurs zalecany w trakcie szkolenia nowych użytkowników Google Cloud. Ukończenie go pozwoli użytkownikowi z niewielkim doświadczeniem lub bez niego uzyskać praktyczną wiedzę, którą będzie mógł zastosować w swoim pierwszym projekcie Google Cloud. Kurs jest wprowadzeniem do podstawowych funkcji Google Cloud i obejmuje między innymi pisanie poleceń Cloud Shell i wdrażanie pierwszej maszyny wirtualnej, a także uruchamianie aplikacji w środowisku Kubernetes Engine lub z równoważeniem obciążenia. Jeśli ukończysz ten kurs wraz z Challenge Lab na końcu, otrzymasz cyfrową plakietkę Google Cloud. Przez kluczowe pojęcia dotyczące poszczególnych modułów przeprowadzą Cię 1-minutowe filmy..

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In this introductory-level Quest, you will get hands-on practice with the Google Cloud’s fundamental tools and services. Google Cloud Essentials is the recommended first Quest for the Google Cloud learner - you will 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. 1-minute videos walk you through key concepts for each lab.

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Chcesz zwiększyć zakres swoich analiz danych bez konieczności zarządzania serwerem z bazą danych? Poznaj sprawdzone metody wykonywania zapytań i uzyskiwania statystyk ze swojej hurtowni danych dzięki tej interaktywnej serii modułów dotyczących BigQuery. BigQuery to w pełni zarządzana i zautomatyzowana baza danych Google pozwalająca przeprowadzać analizę danych niskim kosztem. Umożliwia przeszukiwanie terabajtów danych bez konieczności zarządzania infrastrukturą czy zatrudniania administratora bazy danych. BigQuery używa języka SQL i może wykorzystywać model płatności według wykorzystania. Dzięki BigQuery możesz skupić się na analizowaniu danych i znajdowaniu przydatnych statystyk. Jeśli ukończysz ten kurs wraz z Challenge Lab na końcu, otrzymasz cyfrową plakietkę Google Cloud.

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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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