Viktoriia Dvornyk
Member since 2023
Silver League
11300 points
Set Up an App Dev Environment on Google Cloud
Earned марта 30, 2023 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned марта 30, 2023 EDT
Derive Insights from BigQuery Data
Earned марта 29, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned марта 29, 2023 EDT
Automate Interactions with Contact Center AI
Earned марта 28, 2023 EDT
Share Data Using Google Data Cloud
Earned марта 27, 2023 EDT
Build a Data Warehouse with BigQuery
Earned марта 27, 2023 EDT
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned марта 24, 2023 EDT
Migrate MySQL Data to Cloud SQL Using Database Migration Service
Earned марта 21, 2023 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI
Earned марта 19, 2023 EDT
Develop Your Google Cloud Network
Earned марта 18, 2023 EDT
Use Machine Learning APIs on Google Cloud
Earned марта 18, 2023 EDT
Perform Predictive Data Analysis in BigQuery
Earned февр. 27, 2023 EST
Create ML Models with BigQuery ML
Earned февр. 25, 2023 EST
Prepare Data for ML APIs on Google Cloud
Earned февр. 20, 2023 EST
Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.
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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 Data Studio by connecting to BigQuery data.
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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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Earn a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. 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 the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn a skill badge by completing the Share Data Using Google Data Cloud skill badge course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards.
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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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Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.
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Complete the introductory Migrate MySQL Data to Cloud SQL Using Database Migration Service skill badge course to demonstrate skills in the following: migrating MySQL data to Cloud SQL using different job types and connectivity options available in Database Migration Service and migrating MySQL user data when running Database Migration Service jobs.
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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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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
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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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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 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 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 Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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