Leveraging Google AI APIs Competency (Intermediate Level)

  • 20m
  • 20 questions
The Leveraging Google AI APIs Competency (Intermediate Level) benchmark evaluates your knowledge of utilizing Bard's analytical features and the PaLM 2 API for programmatically accomplishing tasks, including using PaLM models, supported languages, libraries, and communication interfaces. You will be evaluated on your skills in solving code problems with Bard, using the Python client API to integrate PaLM seamlessly, and utilizing advanced features like communication adjustments, response fine-tuning, troubleshooting, security enhancements, and chatbot creation. Learners who score high on this benchmark demonstrate that they have the skills to use Bard's analytical features and can leverage the PaLM API for advanced features and application development.

Topics covered

  • add comments to analyze what code is doing and have Bard fix bugs
  • apply parameters like Temperature, Candidate Count, TopP, and TopK to affect output
  • compare code generated to solve problems in multiple development languages
  • control the output formatting of data in responses
  • create a PaLM API key and verify it works by making a simple request
  • create a simple Chatbot using the API that can answer questions related to a topic
  • define the PaLM API endpoints and their uses
  • distinguish between the different PaLM API model variants and identify the situations in which each should be used
  • identify the features of the PaLM API and how it can be used
  • list the features and capabilities of Bard's analytics
  • outline the Pathways Language Model (PaLM) and how it is used to power Bard
  • outline the use of the Python client application programming interface (API) library for accessing and using PaLM
  • perform a translation to and from English via the API
  • troubleshoot and diagnose issues that can cause problems when using Bard or the API
  • use OAuth 2.0 and other features to improve security and integration with Google services
  • use optimization techniques to reduce resource usage and improve performance
  • use the API to ask questions and get responses
  • use the API to generate text, poems, and stories
  • use the safety filters to check content for explicit material
  • work with Python and the PaLM API to simulate a chat about a topic using context