February 23, 2026

Last year, I decided to study for another Databricks certification. I was initially unsure about taking the exam, but I chose to study for it so I could learn more about developing generative AI applications on the platform.

This exam took about two months of modest studying. The study material was novel to me, as I lacked the experience developing AI and LLM-based applications, especially on the platform. I expected the exam to be harder than the data engineering and machine learning ones. While it ended up not being as difficult as I thought, I still dedicated more time to it.

As with the other certifications I prepared for, the first step was reviewing the exam guide. The exam guide is a kind of compass for what you should study and what is important for the exam. Then comes the learning material for the exam. Databricks offers a Learning Academy that provides courses that teach technical solutions. Databricks made the platform available for free to anyone last year. I recommend utilizing this as a resource to learn more about the generative AI solutions you can create on the platform.

If you’re already experienced with generative AI concepts like RAG, prompting, developing, and deploying LLM applications, you should already have an advantage on the exam. If not, I would suggest learning more about those topics to deepen your understanding. Databricks offers courses on these topics, in addition to other sites such as Coursera. It would also help to create small projects, utilizing the Databricks platform. Databricks also offers a Free Edition where you can practice different concepts.

As with most certifications, they are nearly useless for the purpose of resume building and cute LinkedIn posts. You have to put into practice the stuff you learned. Overall, I enjoyed the process of learning about the capabilities Databricks offers for building generative AI applications.

I linked below some resources to help me study including my personal study guide.

Resources