There are over 400+ Apache Spark courses on Udemy that are rated above 4.5/5. Udemy Apache Spark courses are suitable for anyone including experienced Apache Spark developers or students who do not have any prior knowledge about Apache Spark. Spark SQL, Spark Streaming, machine learning, etc. are the topics covered in the majority of Apache Spark courses.
The article mentions the best Apache Spark courses on Udemy as per the student enrolment rate and ratings. Udemy online courses are priced between USD 50 and USD 200, offering flexibility for different budget levels. Students can enrol now and get an exclusive discount of up to 90% off the regular price by clicking the join now links below.
1. Apache Spark with Scala – Hands on with Big Data!
This course will teach you how to use Apache Spark to process big data using the Scala programming language. You will learn how to install and configure Spark, work with Spark Data Frames, use Spark SQL, build machine learning models with Spark MLlib, and stream data with Spark Streaming.
- Course Rating: 4.7/5
- Duration: 9 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 69 video lectures, 4 articles, downloadable resources, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Apache Spark with Scala – Hands on with Big Data!
Learning Outcomes
| Install and configure Spark | Learn how to install and configure Spark on your local machine or in the cloud. |
| Work with Spark DataFrames | Learn how to create, read, write, and manipulate Spark DataFrames. |
| Use Spark SQL | Learn how to use Spark SQL to query and analyze data. |
| Build machine learning models with Spark MLlib | Learn how to build machine learning models using Spark MLlib. |
2. Apache Spark 3 & Big Data Essentials in Scala | Rock the JVM
Spark Essentials is a comprehensive course that teaches you the basics of Apache Spark. The course covers Spark’s architecture, programming model, and APIs. It also covers how to use Spark for data processing and analysis.
- Course Rating: 4.7/5
- Duration: 7.5 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 25 video lectures, Full lifetime access on Mobile and TV, Certificate of completion from Udemy
Join Now: Apache Spark 3 & Big Data Essentials in Scala | Rock the JVM
Learning Outcomes
| Understand Spark’s architecture | Learn about Spark’s core concepts, such as Resilient Distributed Datasets (RDDs), DataFrames, and SQL |
| Learn Spark’s programming model | Learn how to write Spark code using Scala, Python, or Java |
| Learn Spark’s APIs | Learn how to use Spark’s APIs for data processing and analysis |
| Get hands-on experience with Spark | Work through a series of hands-on exercises to solidify your understanding of Spark |
3. Apache Spark 3 for Data Engineering & Analytics with Python
Microsoft Power BI is the most user-friendly reporting solution available today, with features such as data analysis and interactive visualisation. Author shows you how to effortlessly migrate your Primavera programmes to a sophisticated dashboard to gain a comprehensive understanding of your projects and drive business choices. Author also teaches you how to publish your dashboards and access them by smartphone, tablet, or desktop.
- Course Rating: 4.7/5
- Duration: 8.5 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 89 video lectures, 12 downloadable resources,4 articles, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Apache Spark 3 for Data Engineering & Analytics with Python
Learning Outcomes
| Understand the basics of Python | Learn about Python’s data structures, algorithms, and functions |
| Learn how to use Python for big data engineering | Learn how to use Python to process and analyze large datasets |
| Get hands-on experience with Python and Spark | Work through a series of hands-on exercises to solidify your understanding of Python and Spark |
| Understand the basics of Python | Learn about Python’s data structures, algorithms, and functions |
4. Apache Spark for Java Developers
This course teaches you how to use Apache Spark to process large datasets in Java. It covers the basics of Spark, including Spark Core, SparkSQL, and DataFrames. You will also learn how to use Spark to perform common data processing tasks, such as data cleaning, data transformation, and data analysis..
- Course Rating: 4.6/5
- Duration: 21.5 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 143 video lectures, Full lifetime access on Mobile and TV, Certificate of completion from Udemy
Join Now: Apache Spark for Java Developers
Learning Outcomes
| Start with the basics of Apache Spark | Learn about the core concepts of Spark, such as RDDs, DAGs, and executors. |
| Use SparkSQL to process structured data | Learn how to use SparkSQL to read, write, and manipulate structured data. |
| Use DataFrames to process semi-structured data | Learn how to use DataFrames to read, write, and manipulate semi-structured data. |
| Perform common data processing tasks with Spark | Learn how to use Spark to perform common data processing tasks, such as data cleaning, data transformation, and data analysis |
5. Master Apache Spark – Hands On!
This course will teach you how to use Apache Spark with Java. You will learn about the basics of Spark, as well as how to use Spark with Java to process big data.
- Course Rating: 4.6/5
- Duration: 7 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 32 video lectures, 6 downloadable resources,5 articles, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Master Apache Spark – Hands On!
Learning Outcomes
| Understand the basics of Apache Spark | Apache Spark is a powerful distributed processing framework. It can be used to process large datasets quickly and efficiently. |
| Use Apache Spark with Java | Apache Spark can be used with Java to process big data. Java is a popular programming language that is used for a variety of applications. |
| Process big data with Apache Spark | Apache Spark can be used to process a wide variety of data, including structured, semi-structured, and unstructured data. It can also be used to process data from a variety of sources, including databases, Hadoop, and Hive |
6. Apache Spark 3 – Real-time Stream Processing using Python
This course will teach you how to use Apache Spark to stream data in real time using Python. You will learn how to create Spark streaming applications, process data from different sources, and build machine learning models on streaming data.
- Course Rating: 4.6/5
- Duration: 4.5 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 35 video lectures,2 articles, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Apache Spark 3 – Real-time Stream Processing using Python.
Learning Outcomes
| Understand with the basics of Spark streaming | Learn about the different components of Spark streaming, such as receivers, sources, sinks, and transformations. |
| Create Spark streaming applications | Learn how to create Spark streaming applications using the PySpark API. |
| Process data from different sources | Learn how to process data from different sources, such as Kafka, Flume, and HDFS. |
| Build machine learning models on streaming data | Learn how to build machine learning models on streaming data using Spark MLlib. |
7. Apache Spark 3 – Spark Programming in Python for Beginners
Apache Spark Programming in Python for Beginners is a comprehensive course that teaches you how to use Spark for data processing and analysis. The course covers the basics of Spark, including RDDs, DataFrames, and SQL. It also covers how to use Spark with Python.
- Course Rating: 4.5/5
- Duration: 16 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 74 video lectures, Beginner Skill Level,14 downloadable resources,2 articles, Full lifetime access on Mobile and TV, Certificate of completion from Udemy
Join Now: Apache Spark 3 – Spark Programming in Python for Beginners
Learning Outcomes
| Understand the basics of Spark | Learn about RDDs, DataFrames, and SQL |
| Learn how to use Spark with Python | Learn how to write Spark code in Python |
| Learn how to process and analyze big data | Learn how to use Spark to process and analyze large datasets |
| Get hands-on experience with Spark | Work through a series of hands-on exercises to solidify your understanding of Spark |
8. Scala and Spark for Big Data and Machine Learning Course
‘Learn Scala and Spark to analyse big data’ course will teach you the basics of Scala programming, Spark, and machine learning. You will also learn how to use Spark to analyse financial data and classify ecommerce customer behaviour. You will learn how to analyse financial data and classify ecommerce customer behaviour. This course is a great way to learn the skills needed to analyse big data. With Scala and Spark, It is possible to build powerful applications that can process and analyse large amounts of data.
- Course Rating: 4.5/5
- Duration: 10 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 80 video lectures, 12 articles, 5 downloadable resources, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Scala and Spark for Big Data and Machine Learning Course
Learning Outcomes
| Use Scala for Programming | Learn the basics of the Scala programming language, including its syntax, features, and libraries. |
| Use Spark 2.0 Data Frames to read and manipulate data | Learn how to read and manipulate data using Spark 2.0 Data Frames. |
| Use Spark to Process Large Datasets | Learn how to process large datasets using Spark. |
| Understand how to use Spark on AWS and Data Bricks | Learn how to use Spark on AWS and Data Bricks. |
9. Apache Spark Hands on Specialization for Big Data Analytics
This course is a hands-on introduction to Apache Spark, a unified analytics engine for large-scale data processing. It covers the basics of Spark, including its architecture, programming model, and APIs. The course also includes a number of hands-on exercises that will help you learn how to use Spark to process large datasets.
- Course Rating: 4.1/5
- Duration: 12 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 73 video lectures, 6 downloadable resources, 4 articles, 1 practice test, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Apache Spark Hands on Specialization for Big Data Analytics
Learning Outcomes
| Understand with the basics of Apache Spark | Learn about the architecture, programming model, and APIs of Spark. |
| Use Spark to process large datasets | Learn how to use Spark to process large datasets using its various APIs. |
| Gain hands-on experience with Spark | Complete a number of hands-on exercises that will help you learn how to use Spark. |
| Improve your skills in big data analytics | Improve your skills in big data analytics by learning how to use Spark. |
10. Master Apache Spark using Spark SQL and PySpark 3
This course teaches you how to create and update project baselines. You will learn how to use baselines to track project progress and identify variances. You will also learn how to use Primavera P6 to manage changes to project plans.
- Course Rating: 3.9/5
- Duration: 32 hours
- Price: INR 2,000 – INR 4,000 (click on the join now link to get 90% discount)
- Benefits: 346 video lectures, 2 downloadable resources, Full lifetime access on Mobile and TV, Certificate of completion from Udemy.
Join Now: Master Apache Spark using Spark SQL and PySpark 3
Learning Outcomes
| Understand the basics of Spark SQL | Spark SQL is a powerful tool for processing structured data. It allows you to query data using SQL, and it also provides a number of features that make it easy to process large datasets. |
| Use Spark SQL to process structured data | Spark SQL can be used to process a wide variety of structured data, including CSV files, JSON files, and Parquet files. It can also be used to process data from a variety of sources, including databases, Hadoop, and Hive. |
| Use PySpark 3 to process unstructured data | PySpark 3 is a powerful tool for processing unstructured data. It allows you to use Python to interact with Spark, and it also provides a number of features that make it easy to process large datasets. |
Taming Big Data with Apache Spark and Python – Hands-on!
This course offers hands-on training in Apache Spark and PySpark for big data analysis. It is suitable for students with some prior programming experience, especially Python. The course, now updated for Spark 3, focuses on DataFrames and Structured Streaming. It teaches students to tackle big data challenges by using Spark to extract insights from large datasets. The instructor, an ex-engineer and senior manager from Amazon and IMDb, guides students through over 20 real-world examples.
- Course Rating: 4.6/5
- Duration: 7 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 4 articles, 26 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Taming Big Data with Apache Spark and Python – Hands-on!
Learning Outcomes
| Use DataFrames and Structured Streaming in Spark 3 | Use the MLLib machine learning library to answer common data mining questions |
| Understand how Spark Streaming lets you process continuous streams of data in real-time | Frame big data analysis problems as Spark problems |
| Use Amazon’s Elastic MapReduce service to run your job on a cluster with Hadoop YARN | Install and run Apache Spark on a desktop computer or on a cluster |
| Use Spark’s Resilient Distributed Datasets to process and analyze large data sets across many CPUs | Implement iterative algorithms such as breadth-first-search using Spark |
| Implement iterative algorithms such as breadth-first-search using Spark | Tune and troubleshoot large jobs running on a cluster |
| Share information between nodes on a Spark cluster using broadcast variables and accumulators | Understand how the GraphX library helps with network analysis problems |
Streaming Big Data with Spark Streaming and Scala
This comprehensive course introduces Spark Streaming, a technology for processing real-time big data. It requires a personal computer and provides software installation guidance for Scala IDE, Spark, and a JDK. It includes a Scala crash course and teaches how to set up and analyze streaming data, work with real-time machine learning, and deploy Spark Streaming to a Hadoop cluster. Beginners in programming should consider an introductory course first.
- Course Rating: 4.7/5
- Duration: 6.5 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 3 articles, access on mobile and TV, certificate of completion
Join Now: Streaming Big Data with Spark Streaming and Scala
Learning Outcomes
| Process massive streams of real-time data using Spark Streaming | Integrate Spark Streaming with data sources, including Kafka, Flume, and Kinesis |
| Use Spark 2’s Structured Streaming API | Create Spark applications using the Scala programming language |
| Output transformed real-time data to Cassandra or file systems | Integrate Spark Streaming with Spark SQL to query streaming data in real time |
| Train machine learning models with streaming data, and use those models for real-time predictions | Ingest Apache access log data and transform streams of it |
| Receive real-time streams of Twitter feeds | Maintain stateful data across a continuous stream of input data |
| Query streaming data across sliding windows of time | – |
Apache Spark 2.0 with Java -Learn Spark from a Big Data Guru
This course is designed for students who know how to program in Java. It offers comprehensive training in Apache Spark with Java, covering key concepts and practical examples. The course includes over 10 hands-on examples, such as aggregating weblogs, analyzing real estate data, and working with Stack Overflow survey data. Participants will gain insights into Spark’s architecture, RDD transformations, Spark SQL, and advanced optimization techniques.
- Course Rating: 4.4/5
- Duration: 3.5 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 15 articles, 1 downloadable resource, access on mobile and TV, certificate of completion
Join Now: Apache Spark 2.0 with Java -Learn Spark from a Big Data Guru
Learning Outcomes
| An overview of the architecture of Apache Spark. | Work with Apache Spark’s primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets. |
| Develop Apache Spark 2.0 applications using RDD transformations and actions and Spark SQL. | Develop Apache Spark 2.0 applications using RDD transformations and actions and Spark SQL. |
| Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding about Spark SQL. | Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators. |
| Advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs. | Best practices of working with Apache Spark in the field. |
Spark SQL and Spark 3 using Scala Hands-on with Labs
This course is designed for students with basic programming knowledge who want to learn Data Engineering using Spark SQL and Spark Data Frame APIs with Scala. It provides comprehensive training in building data engineering pipelines. The course covers various topics like setting up a Big Data environment, including an AWS Cloud9 instance, Docker, Jupyter Lab, and key components like Hadoop, Hive, YARN, and Spark. The course focuses on using Spark SQL and Data Frame APIs for data processing, with hands-on tasks and exercises.
- Course Rating: 4.5/5
- Duration: 24 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 32 articles, 7 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Spark SQL and Spark 3 using Scala Hands-on with Labs
Learning Outcomes
| All the HDFS Commands that are relevant to validate files and folders in HDFS. | Enough Scala to work on Data Engineering Projects using Scala as a Programming Language |
| Spark Dataframe APIs to solve the problems using Dataframe style APIs. | Basic Transformations such as Projection, Filtering, Total as well and Aggregations by Keys using Spark Dataframe APIs |
| Inner as well as outer joins using Spark Data Frame APIs | Ability to use Spark SQL to solve the problems using SQL style syntax. |
| Basic Transformations such as Projection, Filtering, Total as well as Aggregations by Keys using Spark SQL | Inner as well as outer joins using Spark SQL |
| Basic DDL to create and manage tables using Spark SQL | Basic DML or CRUD Operations using Spark SQL |
| Create and Manage Partitioned Tables using Spark SQL | Manipulating Data using Spark SQL Functions |
| Advanced Analytical or Windowing Functions to perform aggregations and ranking using Spark SQL | – |
Apache Spark 3 – Spark Programming in Scala for Beginners
This course is designed for candidates who are familiar with programming using the Scala programming language and have access to a recent 64-bit Windows, Mac, or Linux operating system with 8 GB of RAM. The course introduces Apache Spark 3 and Spark programming in Scala. The course follows a hands-on approach, with live coding sessions to explain fundamental concepts. It is ideal for software engineers, data architects, data engineers, managers, and architects involved in data engineering projects using Apache Spark and looking to expand their skills.
- Course Rating: 4.5/5
- Duration: 8 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 2 articles, 53 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Apache Spark 3 – Spark Programming in Scala for Beginners
Learning Outcomes
| Apache Spark Foundation and Spark Architecture | Data Engineering and Data Processing in Spark |
| Working with Data Sources and Sinks | Working with Data Frames, Data Sets and Spark SQL |
| Using IntelliJ Idea for Spark Development and Debugging | Unit Testing, Managing Application Logs and Cluster Deployment |
Apache Spark 3 – Beyond Basics and Cracking Job Interviews
This course is designed for candidates with basic knowledge of Spark programming in Python (PySpark). It focuses on advanced Spark skills and aims to help students prepare for Databricks Spark certification and job interviews. The course covers concepts that are commonly asked in Spark job interviews and certification exams.
- Course Rating: 4.7/5
- Duration: 4 hours
- Price: Join now and get up to 90% off the original price
- Benefits: Access on mobile and TV, certificate of completion
Join Now: Apache Spark 3 – Beyond Basics and Cracking Job Interviews
Learning Outcomes
| Apache Spark 3 Advanced Topics and Concept | Deep Dive in to Spark 3 Architecture and Memory Management |
| Learn AQE, DPP, Broadcast, Accumulators, and Multithreading in Spark 3 | Common Job Interview Questions and Answers |
Databricks Fundamentals & Apache Spark Core
This course is designed for students with basic knowledge of Scala and SQL and aims to teach Databricks and Apache Spark 2.4 and 3.0.0. It focuses on writing Spark applications using Scala and SQL, with a primary emphasis on the DataFrame API and SQL for various data manipulation tasks. Students will gain the skills to write and run Apache Spark code in Databricks, read and write data from the Databricks File System (DBFS), and understand how Apache Spark operates on a cluster with multiple nodes.
- Course Rating: 4.5/5
- Duration: 12 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 1 article, 5 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Databricks Fundamentals & Apache Spark Core
Learning Outcomes
| Databricks | Apache Spark Architecture |
| Working with User Defined Functions | Use the DataFrameWriter API |
| Selecting, and manipulating columns of a DataFrame | Filtering, dropping, sorting rows of a DataFrame |
| Apache Spark SQL | Apache Spark DataFrame API |
| Joining, reading, writing and partitioning DataFrames | Aggregating DataFrames rows |
Apache Spark 3 – Databricks Certified Associate Developer
This course is aimed at candidates with basic Scala and data skills. The course is taught by a Databricks Certified Associate Developer. The course covers Apache Spark’s architecture, core APIs, and data manipulation techniques like joins, unions, and group-by operations. Notebooks containing course-related source code are provided for download, and quizzes help learners assess their understanding of the material.
- Course Rating: 4.6/5
- Duration: 4.5 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 1 practice tests, 2 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Apache Spark 3 – Databricks Certified Associate Developer
Learning Outcomes
| How you can save the result of complex data transformations to an external storage system | The different deployment modes of an Apache Spark Application |
| Learn how Apache Spark runs on a cluster of computer | The Architecture of an Apache Spark Application |
| Create DataFrame from files and Scala Collections | Learn the Execution Hierarchy of Apache Spark |
| Spark DataFrame API and SQL functions | Learn the different techniques to select the columns of a DataFrame |
| How to define the schema of a DataFrame and set the data types of the columns | Apply various methods to manipulate the columns of a DataFrame |
| How to filter your DataFrame based on specifics rules | Learn how to sort data in a specific order |
| Learn how to sort rows of a DataFrame in a specific order | How to arrange the rows of DataFrame as groups |
| How to handle NULL Values in a DataFrame | How to use JOIN or UNION to combine two data sets |
| Working with UDFs and Spark SQL functions | How to use Databricks Community Edition to write Apache Spark Code |
| How to prepare for the Databricks Certified Associate Developer For Apache Spark 3 Certification Exam | – |
Apache Spark Streaming with Python and PySpark
The course focuses on Apache Spark streaming with Python using PySpark, teaching the fundamentals and skills needed to develop Spark streaming applications for big data processing and analytics. It is specifically designed for Python developers looking to enhance their data streaming skills, or Spark developers aiming to upskill. The course covers various topics including scaling up Spark Streaming applications, integrating with tools like Apache Kafka, and connecting to data sources like AWS Kinesis. Through this course, students will gain a comprehensive understanding of Spark streaming, including architecture, RDD transformations and actions, Spark SQL, and data optimization techniques.
- Course Rating: 4.1/5
- Duration: 3.5 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 6 articles, 35 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Apache Spark Streaming with Python and PySpark
Learning Outcomes
| Create big data streaming pipelines with Spark using Python | Run analytics on live Tweet data from Twitter |
| Integrate Spark Streaming with tools like Apache Kafka, used by Fortune 500 companies | Work with new features of the most recent version of Spark: 2.3 |
Apache Spark in-Depth (Spark with Scala)
This comprehensive course covers Apache Spark comprehensively, from basic word count programs to batch processing, Spark Structured Streaming, application development, debugging, performance tuning, optimization, and troubleshooting. The course aims to help individuals advance their careers in data engineering, big data, Hadoop, and Spark, making it suitable for those already working in these fields looking to solidify their understanding. While prior knowledge of Hadoop and Scala basics is helpful, it’s an ideal starting point for learning Apache Spark.
- Course Rating: 4.5/5
- Duration: 40.5 hours
- Price: Join now and get up to 90% off the original price
- Benefits: 34 downloadable resources, access on mobile and TV, certificate of completion
Join Now: Apache Spark In-Depth (Spark with Scala)
Learning Outcomes
| Apache Spark from scratch to in-depth, starting from simple word count program to Batch Processing to Spark Structure Streaming, Performance Tuning | Completing this course will also make you ready for most interview questions |
| Includes Optional Project and path to success | – |
Best Apache Spark Courses on Udemy: FAQs
Ques. Are there any free Apache Spark courses available?
Ans. Udemy offers both paid and free Primavera courses. While paid courses often provide more comprehensive content and additional resources, you can find free Apache spark courses by filtering search results on Udemy to display only free courses. Keep in mind that the content and quality of free courses may vary.
Ques. Can I earn a certificate upon completing a Udemy Apache Spark course?
Ans. Udemy offers certificates of completion for many courses, but it ultimately depends on the course instructor. Check the course details to see if a certificate is mentioned. Keep in mind that Udemy certificates are not accredited academic qualifications but can still be a valuable addition to your professional portfolio.
Ques. Can I interact with the instructors in Udemy Apache Spark courses?
Ans. Yes, Udemy provides a platform for learners to interact with instructors through various means. You can ask questions, seek clarification, or request additional support using the course’s Q&A section. Additionally, some instructors may offer discussion boards or provide direct messaging options for further communication.
Ques. What if I’m not satisfied with a Udemy Apache Spark course I purchased?
Ans. Udemy offers a 30-day money-back guarantee for most courses, including Apache Spark courses. If you are unsatisfied with a course you purchased, you can request a refund within 30 days of purchase. However, be sure to review the refund policy on the course page as some courses may have different refund conditions.
Ques. Can I access Udemy Apache Spark courses after completing them?
Ans. Yes, once you enroll in a Udemy Apache Spark course, you typically have lifetime access to the course materials. This means you can revisit the course content, access updates made by the instructor, and review the material even after you have completed the course. You can refer back to the course as a resource whenever needed.
Ques. What is Apache Spark?
Ans. Apache Spark is an open-source, fast, and general-purpose cluster computing framework for big data processing and analytics.
Ques. What are the key components of Apache Spark?
Ans. The key components of Apache Spark include Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX, each catering to specific data processing needs.
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