Free training for Generative AI Engineering with Databricks 2025

[alisyed]

Hi People, 

I am looking for a self paced training required to prepare and pass the Generative AI Engineering certification in 2025 April/May. The old training has been expired.

Could you please help. 

Appreciate for your support! 
Ali

[TheRealOliver]

Hi,

The Databricks Certified Generative AI Engineer Associate exam information page mentions that there is a series of self-paced courses in Databricks Academy.

You can login to Databricks Academy from this page: https://www.databricks.com/learn/training/login 

Once you log in, search for "Generative AI Pathway" using the form at the top:

 That learning plan includes the four classes that you will have seen mentioned on the exam info page:

• Generative AI Solution Development
• Generative AI Application Development
• Generative AI Application Evaluation and Governance
• Generative AI Application Deployment and Monitoring

The self-paced courses are free. I hope this helps!

[alisyed]

Thank you @TheRealOliver these are what i was looking for. Each of these course is 2 hours, so 8 hours of the training in total, do you think is that sufficient to prepare and pass for the certification exam? 

[Louis_Frolio]

To prepare effectively, you should master the content covered in the four recommended courses and gain at least six months of hands-on experience implementing generative AI functionality on the Databricks platform. Additionally, I recommend becoming familiar with the official Databricks documentation related to generative AI to ensure you are up to date with best practices and platform capabilities.

I hope this helps.

Best regards,
Louis

[TheRealOliver]

I'm glad I could help! 🙂

The answer to your follow-up question can be very different depending on your level of experience and academic aptitude. The course materials are not expected to align 100% with the exam objectives and I second what @Louis_Frolio has said - adding some practical experience on top of academic study is best practice.

[alisyed]

The question is how can I get hands on experience of 6 months if our company is not using data bricks?

How do I get access to tools to privately build projects? 

Thank you 

[Sofiaya]

Hey everyone,

I have  Databricks &  loving how powerful the platform is for managing data & running ML workflows. I am exploring how generative AI is being applied in real-world scenarios within the Databricks ecosystem.

I have gone through a few tutorials and notebooks but most of them are pretty high-level or generic. I want to know—has anyone here implemented any cool generative AI use cases using Databricks?? such as maybe generating synthetic data, text summarization or even code generation?

Also, if you have taken any good hands-on Generative AI Course that integrates well with Databricks or focuses on building projects from scratch, I want your suggestions. Something project-based & not too academic would be ideal.

Thank you..... 😊

[Louis_Frolio]

Here are some Real-World GenAI Use Cases implemented by Databricks customers.

Synthetic Data Generation

This is probably one of the most practical applications I’ve encountered. Databricks has some excellent tools for this:

• Databricks Labs Data Generator (dbldatagen): This is a Python library specifically designed for generating synthetic data at scale using Spark. It supports generating billions of rows within minutes and can create repeatable, predictable data that’s perfect for testing, benchmarking, and demos.
• Enterprise Use Cases: Companies are leveraging Databricks’ synthetic data capabilities for AI agent evaluation and testing. The platform now includes synthetic data generation APIs that significantly reduce time to improve agent quality and deployment.
• Privacy-Safe Collaboration: Some organizations use synthetic data in Databricks Clean Rooms to share insights without exposing sensitive information. You can generate differentially private synthetic data that preserves statistical properties while ensuring privacy.

Text Summarization

Databricks has built-in AI functions that make this incredibly straightforward:

• ai_summarize() Function: You can now invoke state-of-the-art generative AI models directly in SQL to summarize text. It’s as simple as `SELECT ai_summarize(content, max_words)` and works great for processing large datasets.
• Enterprise Applications: Companies are using these AI functions to analyze customer reviews, process documents, and create automated summaries at scale.

Code Generation & AI Agents

This is where things get really exciting:

• Multi-Agent Systems: Databricks supports building sophisticated AI agents using frameworks like LangChain, LangGraph, and pure Python. You can create tool-calling agents that can generate code, make decisions, and execute complex workflows.
• Real Enterprise Examples: Block (Square) uses Databricks GenAI for automated content generation including marketing emails, item descriptions, and website copy. They’ve achieved 12x reduction in computing costs while building these capabilities.

Here are more of our public facing customer use cases:

https://www.databricks.com/blog/data-ai-use-cases-worlds-leading-companies

https://www.databricks.com/blog/data-intelligence-action-100-data-and-ai-use-cases-databricks-custom...

Hope this helps, Lou.