Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
Więcej informacji
Build AI agents that can leverage enterprise databases using the MCP Toolbox for Databases. You will define secure database interaction tools, and implement intelligent querying capabilities (leveraging vector embeddings, structured queries).
Więcej informacji
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 Managed Service for Apache Spark, a także wywoływanie interfejsów API dotyczących uczenia maszynowego, w tym Cloud Natural Language API, Google Cloud Speech-to-Text API oraz Video Intelligence API.
Więcej informacji
Earn a skill badge by completing the Streaming Analytics into BigQuery skill badge course, where you use Pub/Sub, Dataflow and BigQuery together to stream data for analytics.
Więcej informacji
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.
Więcej informacji
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
Więcej informacji
Develop Gen AI Apps with Gemini and Streamlit
Earned sie 26, 2026 EDT
Build AI Agents with Enterprise Databases
Earned maj 21, 2026 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud
Earned sty 7, 2026 EST
Streaming Analytics into BigQuery
Earned gru 9, 2025 EST
Share Data Using Google Data Cloud
Earned gru 9, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned gru 8, 2025 EST