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Databricks Generative AI Engineer Associate: Practice Exams
7 students
Databricks Generative AI Engineer Associate: Practice Exams
Master Generative AI on Databricks: Build, Deploy & Optimize AI Solutions with LLMs, Vector Search, and MLflow!
Created byAshish Rai
Last updated 4/2025
English
What you'll learn
- In this course, students will master building generative AI solutions on Databricks, focusing on real-world skills for the Generative AI Engineer Associate .
- Students will dive into the Databricks ecosystem, learning to design and deploy generative AI solutions for the Generative AI Engineer Associate certification.
- This course equips students for the Databricks Generative AI Engineer Associate certification by teaching core generative AI concepts and tools.
- Students will unlock the power of generative AI on Databricks, preparing for the Generative AI Engineer Associate certification and beyond.
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Included in This Course
280 questions
Description
Are you ready to master Generative AI and become a Databricks Generative AI Engineer Associate? This course will equip you with the skills to build, deploy, and optimize AI solutions using LLMs (Large Language Models), Vector Search, MLflow, and Model Serving on Databricks.
Why Enroll?
Hands-on real-world projects with Databricks notebooks
Industry-relevant case studies & best practices
Covers all topics required for the Databricks Generative AI Engineer Associate certification
Step-by-step guidance for beginners and professionals
By the end of this course, you’ll have the expertise to implement AI-driven applications, optimize machine learning workflows, and ace the Databricks Generative AI Engineer Associate exam!
Exam Details:
Format: Online proctored certification exam
Number of Questions: 45 multiple-choice
Duration: 90 minutes
Exam Content Breakdown:Design Applications (14%): Crafting prompts, selecting model tasks, and translating business requirements into AI solutions.
Data Preparation (14%): Implementing data chunking strategies, filtering content, and preparing data for RAG applications.
Application Development (30%): Developing tools for data extraction, creating prompts, implementing LLM guardrails, and selecting appropriate models.
Assembling and Deploying Applications (22%): Coding chains, deploying endpoints, and utilizing Databricks features like Vector Search and Model Serving.
Governance (8%): Applying data masking techniques, implementing guardrails, and ensuring compliance with legal requirements.
Evaluation and Monitoring (12%): Assessing model performance, monitoring deployments, and managing costs
Who this course is for:
- The Databricks Generative AI Engineer Associate course is ideal for: AI/ML Engineers – Those working on generative AI, LLMs, and model deployment. Data Scientists – Professionals leveraging Databricks for AI/ML workflows. Data Engineers – Engineers handling data pipelines, vector databases, and AI-driven applications. Software Developers – Those integrating AI models into applications. Cloud & MLOps Engineers – Anyone managing AI models on cloud platforms. Tech Enthusiasts & Learners – People exploring generative AI and Databricks for career growth. If you want to design, deploy, and optimize AI solutions using Databricks, this course is for you!