Are you preparing for the Databricks Certified Generative AI Engineer Associate exam?
This in-depth Databricks Generative AI Engineer Mock Tests course with 11 practice tests and 550+ questions is designed to provide a complete, hands-on simulation of the real certification experience—helping you assess your readiness, build your confidence, and master critical skills in LLM-based application development, deployment, and governance.
The Databricks certification validates your ability to build and manage generative AI applications at scale. It confirms your understanding of Retrieval-Augmented Generation (RAG), data preparation, prompt engineering, LangChain orchestration, AI optimization, and compliance management. This Databricks Generative AI Engineer Associate Practice Tests course delivers the exam-style practice you need to succeed.
Enroll today to build the skills, strategy, and confidence to pass the Databricks Certified Generative AI Engineer Associate exam and drive AI transformation in your organization.
Gururo is a PMI Authorized Training Partner
At-a-glance
Best for
- AI and ML professionals
- Data scientists and NLP engineers
- Software developers
- Anyone Serious
Why Gururo?
- Lowest Cost
- PMI Authorized Training Partner (ATP)
- 24*7 Support
- 365 days access
Course Details
- 11 full-length Databricks AI mock exams
- 550+ challenging questions
- Instant Access
- Certificate of Completion
Highlights
- Realistic Exam Simulation
- Aligned with actual exam blueprint
- Progress Tracking & Review option
- Unlimited Attempts
What You’ll Learn
- Pass the Databricks Certified Generative AI Engineer Associate exam with confidence and efficiency.
- Master foundational concepts in generative AI including prompt engineering, few-shot learning, and Retrieval-Augmented Generation (RAG).
- Design and implement data preparation workflows using chunking, metadata tagging, and optimized embeddings.
- Develop LLM-based applications leveraging LangChain, multi-agent collaboration, and structured chatbot frameworks.
- Configure and deploy AI solutions using Databricks Model Serving, Unity Catalog, and vector databases.
- Apply best practices for scalable and secure AI deployments, including versioning, function-calling agents, and caching.
- Evaluate and optimize AI models by analyzing performance metrics, reducing hallucinations, and improving relevance.
- Enforce AI governance using access control, model lineage, LLMOps, and audit logs.
- Utilize MLflow, Delta Lake, and feature stores to streamline generative AI lifecycle management.
- Simulate real-world exam conditions to refine timing, reduce anxiety, and ensure readiness for exam day.
What You’ll Gain
- Realistic, section-specific questions based on Databricks’ official certification guide.
- Scenario-driven practice covering all key domains: design, development, data prep, deployment, evaluation, and governance.
- Exposure to technologies such as LangChain, MLflow, Delta Lake, and vector databases.
- Confidence through timed simulations and performance feedback.
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Course Requirements / Prerequisites
- No formal prerequisites required—designed to be accessible for professionals with diverse technical backgrounds.
- Basic familiarity with AI/ML and Python programming is beneficial.
- Understanding of NLP concepts and language models will enhance the learning experience.
- Prior exposure to Databricks, cloud platforms (AWS, Azure, GCP), and ML tools is helpful but not essential.
- Willingness to engage with practical, scenario-based problem-solving is essential.
- Access to a computer and internet connection for running mock tests.
- Motivation to gain in-demand generative AI skills and validate them with certification.
- Desire to develop hands-on proficiency in retrieval optimization, vector search, and multi-agent reasoning.
- Openness to learning through both exam practice and strategic feedback.
- Commitment to mastering LLM-centric application development and deployment best practices.
Who Should Take This Course?
- AI and ML professionals seeking to earn the Databricks Certified Generative AI Engineer Associate credential.
- Data scientists and NLP engineers exploring hands-on use of LLMs, RAG, and embedding models.
- Software developers building chatbot and intelligent agent applications using LangChain and function-calling.
- Data engineers and architects managing data pipelines and vector-based retrieval systems.
- Professionals working with MLflow, Unity Catalog, and Delta Lake who want certification-backed recognition.
- AI enthusiasts and practitioners aiming to deepen their understanding of generative AI workflows.
- Candidates preparing for technical interviews and certification exams in the generative AI domain.
- Technical leads seeking to ensure compliance, governance, and deployment readiness for LLMs.
- Cloud practitioners expanding into AI/ML deployments within Databricks.
- Anyone interested in advancing their career in generative AI with structured, exam-aligned preparation.
