Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 36 Minute(s)
Language
English
Taught by
Deepak Goyal, Sourabh Sahu
Rating
1 views
Course Overview
Master RAG, LangChain, Vector Search & MLflow to Build GenAI Apps and Pass the Databricks Certification
Are you ready to crack the Databricks Certified Generative AI Engineer Associate Exam and take your Generative AI skills to the next level?
This hands on course is designed to help you master Databricks tools and frameworks used to build real-world LLM applications and prepare you thoroughly for the official Databricks GenAI certification.
Whether you're a data engineer, ML developer, cloud professional, or AI enthusiast, this course will equip you with the skills and confidence to design, develop, deploy, and monitor end-to-end LLM-powered apps using Databricks.
What You’ll Learn:
The fundamentals of Generative AI, LLMs, and Prompt Engineering
How to build RAG (Retrieval-Augmented Generation) applications using LangChain and Mosaic AI Vector Search
Strategies for chunking and preparing data using Delta Lake and Unity Catalog
How to deploy GenAI apps using MLflow, Model Serving, and Inference APIs
Setting up guardrails, masking, and governance to keep your models safe and compliant
How to monitor GenAI pipelines using MLflow metrics, inference logs, and evaluation tools
How to crack the Databricks Generative AI Engineer certification with real-world examples, mapped exam topics, and practice questions
Why This Course?
100% aligned with the official Databricks exam guide
Practical demos, hands-on projects, and real-world case studies
Covers tools like LangChain, MLflow, Vector Search, Unity Catalog, LLM APIs
Includes mock questions and exam preparation tips
No prior GenAI experience needed — beginner-friendly!
Course Content
- 10 section(s)
- 75 lecture(s)
- Section 1 Introduction to Databricks Generative AI Engineer Associate Exam
- Section 2 Introduction to Generative AI & Databricks Ecosystem
- Section 3 Databricks Access
- Section 4 Prompt Engineering
- Section 5 Retrieval Augmented Generation (RAG)
- Section 6 Unity Catlog
- Section 7 Use Case: Problem Statement
- Section 8 Data Preparation
- Section 9 Data Chunking and Chunking Strategies
- Section 10 Vector Embeddings and Vector Databases
What You’ll Learn
- Confidently crack the Databricks Generative AI Engineer Associate Certification with mock questions and scenario-based practice.
- Design end-to-end Generative AI applications using Large Language Models (LLMs) with Databricks
- Craft effective prompts using real-world frameworks (SALT, RTF, CTF, CoT) to optimize LLM responses.
- Build RAG (Retrieval-Augmented Generation) pipelines using tools like LangChain, LlamaIndex, and Mosaic AI Vector Search.
- Prepare high-quality data by extracting, chunking, and storing it in Delta Lake with Unity Catalog for scalable LLM use.
- Choose and integrate the right models (LLMs, embeddings, tools) based on task, cost, latency, and context window.
- Implement safety guardrails and data governance using prompt sanitization, masking, and Unity Catalog.
- Deploy and monitor LLM apps with MLflow, Model Serving, and inference tracking tools in Databricks.
- Evaluate LLM performance with the right metrics and monitoring strategies to optimize accuracy and cost-efficiency.
- Master Databricks-native tools like Vector Search, Model Registry, Unity Catalog, and AI Functions
Skills covered in this course
Reviews
-
MMarcela Roxana Farcasescu
This is the best course so far available on the platform for this certification. I really appreciate how the trainer explained practically the main steps of creating the Generative AI application in Databricks and how those steps are presented and questioned during the exam. This type of learning is far more important than the certification itself! Thank you a million times for your time and efforts added into this super training!
-
PPrema Kathiresan Vasagam
Good course on the overall LLM journey with real time usecase explanation.
-
VVijay Raghunath
The course and the chapter order need to match to the Databricks Certification Exam. The course structure is not well organized to relate the contents to the Databricks certification, frequently skipping between Databricks and generic Architecture. Multiple choice quizzes do not allow for multiple selections. the course download contents for lessons reference and all downloadable material should be available at one place for downloading preferably as zip file, not scattered all across the course.
-
JJ XX
Overall good to introduce the key concepts with some handson example. This course is recommeneded.
