We are currently experiencing intermittent issues with the Gemini Enterprise labs. Please bear with us while we work on the resolution.
The Google Skills platform will be unavailable for approximately 20 minutes on Sunday, November 8, starting at 7:00 PM EST (12:00 AM UTC, Nov 9). If you have any questions, please contact support-skills@google.com
Erik Alves
Date d'abonnement : 2023
Ligue d'Or
14335 points
[DEPRECATED] Gemini for Data Scientists and Analysts
Earned nov. 5, 2025 EST
Implement Multimodal Vector Search with BigQuery
Earned nov. 5, 2025 EST
Create Embeddings, Vector Search, and RAG with BigQuery
Earned nov. 4, 2025 EST
Work with Gemini Models in BigQuery
Earned nov. 4, 2025 EST
Boost Productivity with Gemini in BigQuery
Earned nov. 4, 2025 EST
BigQuery for Machine Learning
Earned oct. 9, 2025 EDT
BigQuery for Data Analysts
Earned sept. 25, 2025 EDT
Create ML Models with BigQuery ML
Earned fév. 17, 2024 EST
Use Machine Learning APIs on Google Cloud
Earned fév. 17, 2024 EST
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI
Earned fév. 3, 2024 EST
Set Up an App Dev Environment on Google Cloud
Earned fév. 2, 2024 EST
Prepare Data for ML APIs on Google Cloud
Earned fév. 2, 2024 EST
Implementing Cloud Load Balancing for Compute Engine
Earned nov. 25, 2023 EST
In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
En savoir plus
Complete the intermediate Implement Multimodal Vector Search with BigQuery skill badge to demonstrate skills in the following: using Gemini in BigQuery to generate and debug SQL, conduct sentiment analysis, summarize text and identify keywords, generate embeddings, create a Retrieval Augmented Generation (RAG) pipeline, and implement multimodal vector search.
En savoir plus
This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.
En savoir plus
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
En savoir plus
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.
En savoir plus
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.
En savoir plus
This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision making.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
En savoir plus
