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[center]![[Image: 74444aa1b5b289ac29c7e3e735ddd0af.jpg]](https://i127.fastpic.org/big/2026/0516/af/74444aa1b5b289ac29c7e3e735ddd0af.jpg)
Databricks Certified Generative Ai Engineer Associate By Olivier Auffret
Published 5/2026
Created by olivier AUFFRET
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 64 Lectures ( 9h 24m ) | Size: 3.52 GB[/center]
Build GenAI systems that work in production - that are robust, governed, observable, and trusted by organization
What you'll learn
⚡ Build and deploy a complete RAG system on Databricks
⚡ Design and evaluate autonomous AI agents
⚡ Apply rigorous GenAI quality measurement
⚡ Deploy and monitor AI applications in production on Databricks
⚡ Navigate the full Databricks AI ecosystem
⚡ Prepare the Databricks Generative AI Engineer Associate Certification
Requirements
❗ Basic Python programming
❗ Familiarity with SQL
❗ A general understanding of what large language models (LLMs) are
❗ A GitHub account
❗ No prior Databricks experience required
DescriptionThis course contains the use of artificial intelligence.
Welcome to this Databricks Generative AI Engineer certification preparation course!
We'll cover how to break down complex AI problems, select the right tools from the GenAI ecosystem, and master Databricks-specific technologies: Vector Search for semantic retrieval, Model Serving for real-time deployment, MLflow for managing the model lifecycle, and Unity Catalog for data governance - ultimately enabling you to build and deploy RAG applications and LLM chains in production.
For this course, I chose to work with the Databricks Free Edition, a free version accessible to everyone. While it doesn't include features still in beta, I keep it regularly updated. The course blends theoretical presentations with hands-on workshops illustrating key concepts, all grouped together in a GitHub project.
This course is aimed at developers - whether software engineers, data scientists, or data engineers - who have already built POCs using frameworks such as LlamaIndex, LangChain, or CrewAI. If you have a working knowledge of Python and SQL and want to master every step of taking your work to production on Databricks - then validate those skills through certification - this course is for you.
If this is what you're looking for, I invite you to join us. I hope you enjoy exploring all these concepts as much as I did - happy learning!
Who this course is for
⭐ Developer or software engineer who wants to build real AI applications
⭐ Data engineer or data scientist already working on the Databricks platform who wants to extend your skills into generative AI.
⭐ ML engineer or MLOps practitioner looking to transition from classical machine learning to LLMOps.
Homepage
![[Image: 74444aa1b5b289ac29c7e3e735ddd0af.jpg]](https://i127.fastpic.org/big/2026/0516/af/74444aa1b5b289ac29c7e3e735ddd0af.jpg)
Databricks Certified Generative Ai Engineer Associate By Olivier Auffret
Published 5/2026
Created by olivier AUFFRET
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 64 Lectures ( 9h 24m ) | Size: 3.52 GB[/center]
Build GenAI systems that work in production - that are robust, governed, observable, and trusted by organization
What you'll learn
⚡ Build and deploy a complete RAG system on Databricks
⚡ Design and evaluate autonomous AI agents
⚡ Apply rigorous GenAI quality measurement
⚡ Deploy and monitor AI applications in production on Databricks
⚡ Navigate the full Databricks AI ecosystem
⚡ Prepare the Databricks Generative AI Engineer Associate Certification
Requirements
❗ Basic Python programming
❗ Familiarity with SQL
❗ A general understanding of what large language models (LLMs) are
❗ A GitHub account
❗ No prior Databricks experience required
DescriptionThis course contains the use of artificial intelligence.
Welcome to this Databricks Generative AI Engineer certification preparation course!
We'll cover how to break down complex AI problems, select the right tools from the GenAI ecosystem, and master Databricks-specific technologies: Vector Search for semantic retrieval, Model Serving for real-time deployment, MLflow for managing the model lifecycle, and Unity Catalog for data governance - ultimately enabling you to build and deploy RAG applications and LLM chains in production.
For this course, I chose to work with the Databricks Free Edition, a free version accessible to everyone. While it doesn't include features still in beta, I keep it regularly updated. The course blends theoretical presentations with hands-on workshops illustrating key concepts, all grouped together in a GitHub project.
This course is aimed at developers - whether software engineers, data scientists, or data engineers - who have already built POCs using frameworks such as LlamaIndex, LangChain, or CrewAI. If you have a working knowledge of Python and SQL and want to master every step of taking your work to production on Databricks - then validate those skills through certification - this course is for you.
If this is what you're looking for, I invite you to join us. I hope you enjoy exploring all these concepts as much as I did - happy learning!
Who this course is for
⭐ Developer or software engineer who wants to build real AI applications
⭐ Data engineer or data scientist already working on the Databricks platform who wants to extend your skills into generative AI.
⭐ ML engineer or MLOps practitioner looking to transition from classical machine learning to LLMOps.
Homepage
Code:
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