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Databricks Certified Associate Developer for Apache Spark 3 Course that will give you more understanding On Spark

What you will learn

Understanding Apache Spark: Gain a solid understanding of big data processing and the advantages of Apache Spark over traditional data processing frameworks.

Spark Architecture: Learn about the architecture and components of Apache Spark, including Spark Core, Spark SQL

Spark’s Resilient Distributed Datasets (RDDs), and understand transformations and actions in Spark.

Spark SQL and DataFrames: Explore Spark SQL and its features, work with DataFrames and datasets


Databricks Certified Associate Developer for Apache Spark 3: Master Apache Spark with Real-World Projects

Description: Learn Apache Spark 3 from scratch and prepare for the Databricks Certified Associate Developer exam with this comprehensive and hands-on Udemy course. Boost your career and become an Apache Spark expert today!

Introduction: Welcome to the ultimate Udemy course for mastering Apache Spark 3 and preparing for the Databricks Certified Associate Developer exam. If you’re looking to enhance your skills in big data processing and analytics, this course is perfect for you. With hands-on projects, real-world examples, and expert guidance, you’ll gain the knowledge and confidence to excel in the world of Apache Spark.

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Key Features:

  1. Comprehensive Course: Learn Apache Spark 3 from the ground up, covering all essential concepts and advanced topics required to become a certified associate developer.
  2. Hands-On Projects: Apply your knowledge to real-world projects, working with large datasets and gaining practical experience in data processing, analysis, and machine learning with Spark.
  3. Exam Preparation: Get fully prepared for the Databricks Certified Associate Developer exam with dedicated exam-focused sections, practice tests, and tips from certified professionals.
  4. Expert Instructors: Learn from industry experts with extensive experience in Apache Spark and big data analytics, ensuring you receive the highest quality education.
  5. Interactive Learning: Engage in interactive quizzes, coding exercises, and discussions to reinforce your understanding of Apache Spark concepts and techniques.
  6. 24/7 Access: Enjoy lifetime access to the course material, including updates and additional resources, allowing you to learn at your own pace and revisit concepts whenever needed.

Course Curriculum:

  1. Introduction to Apache Spark 3
    • Understanding big data and its challenges
    • Overview of Apache Spark and its Advantages
    • Spark architecture and components
  2. Spark Basics
    • Installing and setting up Spark on your local machine
    • Working with Spark’s Resilient Distributed Datasets (RDDs)
    • Transformations and actions in Spark
    • Hands-on exercises and coding examples
  3. Spark SQL and DataFrames
    • Introduction to Spark SQL and its features
    • Working with DataFrames and datasets
    • Data manipulation and querying using Spark SQL
    • Integration with external data sources (SQL databases, CSV, JSON, etc.)
  4. Databricks Certified Associate Developer Exam Preparation
    • Exam Overview and Requirements
    • Key topics and concepts covered in the exam
    • Tips and strategies for exam success
    • Practice tests and mock exams

Why Choose This Course:

  • Comprehensive and up-to-date curriculum designed to cover all aspects of Apache Spark 3.
  • Hands-on projects ensure you gain practical experience and develop confidence in working with Spark.
  • Exam-focused sections and practice tests prepare you thoroughly for the Databricks Certified Associate Developer exam.
  • Lifetime access to course material allows you to revisit concepts and access future updates.
  • Learn from industry experts who bring real-world experience and insights to the course.



Introduction of Databricks Certified Course
Databricks Exam Structure

Databricks Workspace Creation

Azure Databricks Creation
Understanding Databricks Workspace
Community Edition SignUp
Creating Cluster And Running First Code

Databricks Architecture

Understanding Databricks Architecture

Basics Concepts

Take Aways from Last Lecture
RDD and DataFrame and Dataset
Databricks Transformation and Action

Apache Spark API Creating Dataframes

Creating DataFrame API and Lecture

Selecting DataFrame API

Selecting DataFrame Theory and Practice

Renaming DataFrame API

Renaming DataFrame API

Basic Column Manipulation

Basic Column Manipulation 1
Basic Column Manipulation 2

Dropping API

Drop APIs

Filtering API

Filtering API

Sorting API

Sorting API