• views: 256
• date: 6 April 2026
• posted by: AD-TEAM

Pass Databricks Certified Data Engineer Associate Exam Preparation with Hands-On Labs & HD Quality Video

What you'll learn

Databricks Clusters, Notebooks, data storage

Databricks Lakehouse Platform (architecture, descriptions, benefits)

Delta Lake

ELT with Spark SQL and Python

Relational entities (databases, tables, views)

Accessing Data from Azure Data Lake Storage (ADLS)

Structured Streaming, Auto Loader

Delta Live Tables, Multi-hop Architecture

Databricks Jobs

Databricks Dashboards

Data Governance

Requirements

Basic knowledge of SQL and Python

Basic understanding of cloud fundamentals

Description

Welcome to our comprehensive course on Databricks Certified Data Engineer Associate certification. This course is designed to help you master the skills required to become a certified Databricks data engineer associate.Databricks is a cloud-based data analytics platform that offers a unified approach to data processing, machine learning, and analytics. With the growing demand for data engineers, Databricks has become one of the most sought-after skills in the industry.In this course, you'll learn the core concepts of Databricks, including Databricks Lakehouse Platform, ELT with Spark SQL and Python, Incremental Data Processing, Production Pipelines, and Data Governance.This course is designed by industry experts with years of experience in Databricks and data engineering. This course has theoretical concepts and hands-on labs to help you apply the concepts learned in the course.Upon completion of the course, you'll be able to take the Databricks Certified Data Engineer Associate exam with confidence and succeed in your career as a data engineer.At the end of this course you should be able to:Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools, including:Data Lakehouse (architecture, descriptions, benefits)Data Science and Engineering workspace (clusters, notebooks, data storage)Delta Lake (general concepts, table management, manipulation, optimizations)Build ETL pipelines using Apache Spark SQL and Python, including:Relational entities (databases, tables, views)ELT (creating tables, writing data to tables, cleaning data, combining and reshaping tables, SQL UDFs)Python (facilitating Spark SQL with string manipulation and control flow, passing data between PySpark and Spark SQL)Incrementally process data, including:Structured Streaming (general concepts, triggers, watermarks)Auto Loader (streaming reads)Multi-hop Architecture (bronze-silver-gold, streaming applications)Delta Live Tables (benefits and features)Build production pipelines for data engineering applications and Databricks SQL queries and dashboards, including:Jobs (scheduling, task orchestration, UI)Dashboards (endpoints, scheduling, alerting, refreshing)Understand and follow best security practices, including:Unity Catalog (benefits and features)Entity Permissions (team-based permissions, user-based permissions)Enroll now and take the first step towards becoming a certified Databricks data engineer associate.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Getting started with Databricks

Lecture 2 Bigdata History

Lecture 3 Introduction to Databrics

Lecture 4 Lab: Databricks Workspace with Community Edition

Lecture 5 Lab: Databricks Workspace with Azure Cloud

Lecture 6 Databricks User Interface Overview

Lecture 7 Azure Databricks Architecture Overview

Lecture 8 Resources Created by Azure Databricks Workspace

Section 3: Databricks Clusters

Lecture 9 Introduction to Databricks Cluster

Lecture 10 Databricks Cluster Configuration

Lecture 11 Lab: Creating Databricks Cluster

Lecture 12 Azure Databricks Pricing

Lecture 13 Explore Cluster Feature from UI

Lecture 14 Azure Cost Control

Lecture 15 Databricks Cluster Pool

Lecture 16 Cluster Policies Part - 1

Lecture 17 Cluster Policies Part - 2

Section 4: Databricks Notebooks

Lecture 18 Databricks Notebooks Introduction

Lecture 19 Magic Commands

Section 5: Databricks Lakehouse Platform

Lecture 20 Delta Lake

Lecture 21 Lab : Delta Lake Tables Part - 1

Lecture 22 Lab : Delta Lake Tables Part - 2

Lecture 23 Lab : Delta Lake Advanced Part - 1

Lecture 24 Lab - Delta Lake Advanced Part - 2

Lecture 25 Data objects in Databricks Lakehouse

Lecture 26 Lab - Databases and Tables on Databricks Part - 1

Lecture 27 Lab - Databases and Tables on Databricks Part - 2

Lecture 28 Lab - Databases and Tables on Databricks Part - 3

Lecture 29 Lab - Databases and Tables on Databricks Part - 4

Lecture 30 Views

Section 6: Thank You

Lecture 31 Congratulations & way forward

Anyone who wants to prepare for the Databricks Data Engineer Associate certification exam,Students who wants to peruse a career in Data Engineering,Professionals who wants to move from other technologies to Data Engineering,Anyone who wants to start learning Databricks





   
   
   

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