Mohsin Anees
Membro dal giorno 2025
Campionato Oro
21110 punti
Perform Predictive Data Analysis in BigQuery
Earned feb 14, 2025 EST
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI
Earned feb 14, 2025 EST
Production Machine Learning Systems
Earned feb 13, 2025 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned feb 12, 2025 EST
Monitor and Manage Google Cloud Resources
Earned feb 11, 2025 EST
Use Machine Learning APIs on Google Cloud
Earned feb 11, 2025 EST
The Basics of Google Cloud Compute
Earned feb 7, 2025 EST
Create ML Models with BigQuery ML
Earned feb 7, 2025 EST
[Deprecated] Classify Images with TensorFlow on Google Cloud
Earned feb 7, 2025 EST
Build LookML Objects in Looker
Earned feb 2, 2025 EST
Baseline: dati, ML, AI
Earned gen 30, 2025 EST
Applying Machine Learning to your Data with Google Cloud
Earned gen 29, 2025 EST
Analyze Sentiment with Natural Language API
Earned gen 23, 2025 EST
Viaggio nell'AI generativa - Agent Platform
Earned gen 23, 2025 EST
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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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.
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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
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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 introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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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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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
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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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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.
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Complete the introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.
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Big data, machine learning e intelligenza artificiale sono i principali argomenti di computing trattati attualmente, ma questi campi sono piuttosto specializzati ed è complicato reperire materiale introduttivo. Fortunatamente, Google Cloud offre servizi facili da usare in queste aree e con questo corso di livello introduttivo, in modo da poter fare i primi passi con strumenti come BigQuery, API Cloud Speech e Video Intelligence.
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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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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.
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Il corso Viaggio nell'AI generativa - Agent Platform è una raccolta di lab su come utilizzare l'AI generativa su Google Cloud. Nei lab imparerai a utilizzare i modelli Gemini in Agent Platform. Scoprirai inoltre come progettare i prompt, le best practice da seguire e come utilizzare l'AI generativa per l'ideazione, la classificazione, l'estrazione e il riassunto di testi e molto altro ancora. Imparerai anche come ottimizzare un foundation model addestrandolo tramite addestramento personalizzato in Agent Platform ed eseguendo il deployment su un endpoint in Agent Platform.
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