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Mammoth Club All levels 1 sections 6 lectures

Exam 8 - Databricks Certified Generative AI Engineer Associate

Test your knowledge (with 45+ questions and unlimited attempts!) on Assembling and Deploying Apps: Sequence the steps needed to deploy an endpoint for a basic RAG application, create and query a Vector Search index, identify how to serve an LLM application that leverages Foundation Model APIs, identify resources needed to serve features for a RAG application, explain the key concepts and components of Mosaic AI Vector Search, identify batch inference workloads and apply ai_query() appropriately.

01
Skill level
All levels
02
Sections
1
03
Lectures
6
04
Instructor
Alex Kropf
What's inside

This course includes.

1
Sections
6
Lectures
6
Quizzes
Certificate of completion
Included
Mobile and desktop access
Included
AI learning assistance
Included
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Course content

Curriculum & lectures.

1 sections · 6 lectures
+ Exam 6 lectures
Sequence the steps needed to deploy an endpoint for a basic RAG application Locked
Create and query a Vector Search index Locked
Identify how to serve an LLM application that leverages Foundation Model APIs Locked
Identify resources needed to serve features for a RAG application Locked
Explain the key concepts and components of Mosaic AI Vector Search Locked
Identify batch inference workloads and apply ai_query() appropriately Locked
Instructors

Taught by people who ship.

Alex Kropf

Alex Kropf

Instructor

Alex Kropf is Mammoth Club's CLO, public speaker, consultant, IT author and Senior Software Developer. Alex has produced 1,000+ best-selling courses, books and workshops for Mammoth Club, Course Pro and our clients since 2016.

Ready to start building?

Test your knowledge (with 45+ questions and unlimited attempts!) on Assembling and Deploying Apps: Sequence the steps needed to deploy an endpoint for a basic RAG application, create and query a Vector Search index, identify how to serve an LLM application that leverages Foundation Model APIs, identify resources needed to serve features for a RAG application, explain the key concepts and components of Mosaic AI Vector Search, identify batch inference workloads and apply ai_query() appropriately.

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