Databricks Certified Generative AI Engineer Associate

Intermediate Level

Use Databricks to build performant generative AI solutions
The Databricks Certified Generative AI Engineer Associate certification exam assesses an individual’s ability to design and implement LLM-enabled solutions using Databricks.
This includes problem decomposition to break down complex requirements into manageable tasks as well as choosing appropriate models, tools and approaches from the current generative AI landscape for developing comprehensive solutions.
It also assesses Databricks-specific tools such as Vector Search for semantic similarity searches, Model Serving for deploying models and solutions, MLflow for managing a solution lifecycle, and Unity Catalog for data governance.

Course Summary:

A practical Databricks training that equips engineers and data practitioners to build, govern, deploy, and monitor real-world generative AI applications on the Databricks platform.

This 16-hour intermediate course focuses on developing generative AI solutions with Databricks, including retrieval-based agents, single-agent applications, and comprehensive lifecycle practices. It covers skills in vector search, document processing, embedding generation, RAG workflows, and tools like MLflow and Unity Catalog.

Learners also gain hands-on experience in evaluating, governing, deploying, and monitoring generative AI systems, with emphasis on performance, cost, and operational best practices for production-ready workflows.

Fees:

RM6,750.00

Intakes:

17-20 Mar 2026 | 21-24 Apr 2026

Skills measured:

  • Design Applications

  • Data Preparation
  • Application Development
  • Assembling and Deploying Apps
  • Governance
  • Evaluation and Monitoring

Who is this for?

  • Data Scientists

  • Machine Learning Engineers
  • Data Practitioners

Validate your data and AI skills on Databricks by earning a Databricks credential.

94% of leaders face AI-critical skill shortages today, with one in three reporting gaps of 40% or more
46% of organizations currently integrate workforce planning into their AI roadmaps.
55% of leaders expect significant cost and productivity improvements from agentic AI.

Industry-Recognized Skill Validation

Certifications prove your verified expertise on the Databricks platform and data/AI skills.

Improved Career Opportunities

Certified professionals stand out in job searches and can access more roles in data engineering, analytics, and AI. 

Higher Earning Potential

Certified individuals often command better compensation compared to non-certified peers.

Deeper Technical Competence

Preparing for certification enhances practical mastery of Databricks tools, Spark, and data workflows.

Exam Overview

Category:

Associate

Exam Duration:

90 minutes

Exam Format:

65 questions

Delivery:

Remote proctored or onsite testing center

Cost:

200 USD

Language offered:

English, Japanese, Korean

Recertification:

Every two years to maintain your certified status. To recertify, you must take the current version of the exam

Target Audience:

Data scientists, Machine learning engineers, Data practitioners

Validity:

2 years

Open up new possibilities for your career

Frequently Asked Questions (FAQs)

It signals to employers that you can build, deploy, and manage generative AI applications on the Databricks platform, a skill set in rising demand in AI-driven roles.

Demand for professionals skilled in generative AI and enterprise AI tooling continues to grow as more companies adopt AI solutions, making credentials like this increasingly relevant.

Yes; it can open opportunities in roles such as AI Engineer, Data Scientist with GenAI focus, or AI Solution Architect by validating practical GenAI engineering skills.

Databricks combines unified data and AI workflows used by many enterprises, so mastering it with certification helps bridge data, ML, and AI development competencies.

Professionals with advanced AI and platform-specific certifications typically access higher-paying positions and greater compensation due to specialized skill recognition.

Yes; in AI and data hiring, demonstrated skills and certifications are increasingly valued alongside or even over formal degrees, especially for emerging tech like generative AI.

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