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Domain | Weight (%) | Description |
---|---|---|
Generative AI Fundamentals | 20% | Covers the foundational concepts of generative AI, including generative models, transformers, and ethical considerations. |
Databricks Platform Basics | 15% | Focuses on the essential features of the Databricks platform, including its architecture, workspace setup, and core tools. |
Training Generative AI Models | 25% | Includes techniques for training generative AI models, such as GPT and other transformer-based architectures, using Databricks. |
Data Preparation and Management | 18% | Covers preparing and managing datasets for training generative AI models, including feature engineering and data cleaning. |
Model Deployment and Monitoring | 12% | Focuses on deploying generative AI models in production environments and monitoring their performance using Databricks tools. |
Performance Optimization | 10% | Includes techniques for optimizing generative AI models and pipelines for efficiency and scalability on the Databricks platform. |
The Databricks Databricks-Generative-AI-Engineer-Associate exam validates your expertise in building and managing generative AI solutions using Databricks. It demonstrates proficiency in advanced AI engineering concepts, making it an ideal certification for professionals aiming to excel in the rapidly growing field of generative AI.
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The Databricks Certified Generative AI Engineer Associate exam consists of 60 multiple-choice and scenario-based questions. Candidates are given 120 minutes to complete the test. The questions evaluate knowledge in areas such as generative AI models, Databricks platform features, and AI deployment strategies.
Yes, the Databricks-Generative-AI-Engineer-Associate exam can be taken online. To take the exam online, you need to register through the Databricks certification portal, ensure you meet the technical requirements, and schedule your exam at a convenient time.
While there are no strict prerequisites, it is recommended that candidates have foundational knowledge of AI engineering, experience with Databricks, and familiarity with Python, machine learning, and deep learning concepts.
Generally, Generative AI Engineers with certification tend to have higher salaries compared to their non-certified counterparts, as certification demonstrates a verified level of expertise and knowledge.
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