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"Apache Spark & Scala" courses, certification and training

  1. Data Science Architect Master's Course in Association with IBM

    Our Data Science Architect master's course lets you gain proficiency in Data Science. You will work on real-world projects in Data Science with R, Apache Spark, Scala, Deep Learning, Tableau, Data Science with SAS, SQL, MongoDB and more. In this program, you will cover 12 courses and 48 industry-based projects with 1 CAPSTONE project. As a part of online classroom training, you will receive five additional self-paced courses co-created with IBM namely Deep Learning with TensorFlow, Build Chatbots with Watson Assistant, R for Data Science, Spark MLlIb, and Python for Data Science. Moreover, you will also get an exclusive access to IBM Watson Cloud Lab for Chatbots course.

    Online ClassroomIntermediate
    Enquire Now

    Tableau, Data Science, Machine Learning

    Offered by:  Intellipaat
  2. Apache Spark and Scala (Online Classroom-Flexi Pass)

    Apache Spark is an open-source cluster-computing framework used for Big Data Processing. It combines SQL, streaming and complex analytics together seamlessly to handle a wide range of data processing scenarios. Scala is a general-purpose programming language which is supported by Apache Spark. This Apache Spark and Scala course is designed for candidates who want to advance their skills and expertise in Big Data Hadoop Ecosystem. Designed by experts in the industry, this course offers training on various topics like Spark Streaming, Spark SQL, Machine Learning Programming, GraphX Programming and Shell Scripting Spark. In addition to this, the candidates get to work on real life industry project. Upon completion of this course, successful candidates get experience certificate in Apache Spark and Scala.

    1107 Students
    47 HoursOnline ClassroomIntermediate
    $ 313 Enquire Now

    Big Data, Machine Learning, java, Operations

    Offered by:  Simplilearn
  3. Apache Spark and Scala Certification Training

    Apache Spark is an open-source cluster-computing framework used for Big Data Processing. It combines SQL, streaming and complex analytics together seamlessly to handle a wide range of data processing scenarios. Scala is a general-purpose programming language which is supported by Apache Spark. This Apache Spark and Scala course is designed for candidates who want to advance their skills and expertise in Big Data Hadoop Ecosystem. Designed by experts in the industry, this course offers training on various topics like Spark Streaming, Spark SQL, Machine Learning Programming, GraphX Programming and Shell Scripting Spark. In addition to this, the candidates get to work on real life industry project. Upon completion of this course, successful candidates get experience certificate in Apache Spark and Scala.

    1107 Students
    15 HoursOnline self studyIntermediate
    $ 175 Enquire Now

    Big Data, Machine Learning, java, Operations

    Offered by:  Simplilearn
  4. Spark, Scala and Storm combo

    It is an all-in-course designed to give a 360 degree overview of real-time processing of unbound data streams using Apache Storm and creating applications in Spark using Scala programming. The major topics include concepts of Big Data world, Batch Analysis, Types of Analytics and usage of Apache Storm for real-time Big Data Analytics, Comparison between Spark and Hadoop and Techniques to increase your application performance, enabling high-speed processing.

    8122 Students
    40 Hours Online self studyIntermediate
    $ 234

    Big Data, java, Machine Learning, Law, Operations

    Offered by:  Intellipaat
  5. Taming Big Data with Apache Spark 3 and Python - Hands On!

    New! Updated for Spark 3 and with a hands-on structured streaming example. Big data" analysis is a hot and highly valuable skill and this course will teach you the hottest technology in big data: Apache Spark . Employers including Amazon , EBay , NASA JPL , and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think. Learn and master the art of framing data analysis problems as Spark problems through over 15 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb. Learn the concepts of Spark's Resilient Distributed Datastores Develop and run Spark jobs quickly using Python Translate complex analysis problems into iterative or multi-stage Spark scripts Scale up to larger data sets using Amazon's Elastic MapReduce service Understand how Hadoop YARN distributes Spark across computing clusters Learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX By the end of this course, you'll be running code that analyzes gigabytes worth of information in the cloud in a matter of minutes. This course uses the familiar Python programming language ; if you'd rather use Scala to get the best performance out of Spark, see my "Apache Spark with Scala - Hands On with Big Data" course instead. We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most popular" superhero is and develop a system to find degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer. This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together both on your own system, and in the cloud using Amazon's Elastic MapReduce service. 5 hours of video content is included, with over 15 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX. Wrangling big data with Apache Spark is an important skill in today's technical world. Enroll now! " I studied "Taming Big Data with Apache Spark and Python" with Frank Kane, and helped me build a great platform for Big Data as a Service for my company. I recommend the course! " - Cleuton Sampaio De Melo Jr.

    Online self studyIntermediate
    ₹ 9,600 96% OFF ₹ 450 Take this Course

    Big Data, Cloud Computing, Data Analysis, Machine Learning, Data Science

    Offered by:  UDEMY
  6. Apache Spark Fundamentals

    Apache Spark Fundamentals course introduces to the various components of the spark framework to efficiently process, visualize and analyze data. The course takes you through spark applications using Python, Scala and Java. You will also learn about the apache spark programming fundamentals like resilient distributed datasets and check which operations to be used to do a transformation operation on the RDD. This will also show you how to save and load data from different data sources like different type of files, RDBMS databases and NO-SQL. At the end of the course, you will explore effective spark application and execute it on Hadoop cluster to make informed business decisions.

    3 HoursOnline self studyIntermediate
    $ 65

    java, Operations

    Offered by:  Skillsoft
  7. Apache Spark 2 with Scala - Hands On with Big Data!

    New! Updated for Spark 2.3. ?? Big data" analysis is a hot and highly valuable skill ?? and this course will teach you the hottest technology in big data: Apache Spark . Employers including Amazon , EBay , NASA JPL , and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think, and you'll be learning from an ex-engineer and senior manager from Amazon and IMDb. Spark works best when using the Scala programming language, and this course includes a crash-course in Scala to get you up to speed quickly. For those more familiar with Python however, a Python version of this class is also available: "Taming Big Data with Apache Spark and Python - Hands On". Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples , and then scale them up to run on cloud computing services in this course. Learn the concepts of Spark's Resilient Distributed Datastores Get a crash course in the Scala programming language Develop and run Spark jobs quickly using Scala Translate complex analysis problems into iterative or multi-stage Spark scripts Scale up to larger data sets using Amazon's Elastic MapReduce service Understand how Hadoop YARN distributes Spark across computing clusters Practice using other Spark technologies, like Spark SQL, DataFrames, DataSets, Spark Streaming, and GraphX By the end of this course, you'll be running code that analyzes gigabytes worth of information ?? in the cloud ?? in a matter of minutes. We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most ?? popular" superhero is ?? and develop a system to find ?? degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to SpiderMan? You'll find the answer. This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together ?? both on your own system, and in the cloud using Amazon's Elastic MapReduce service. 7.5 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX. Enroll now, and enjoy the course! "I studied Spark for the first time using Frank's course "Apache Spark 2 with Scala - Hands On with Big Data!". It was a great starting point for me, gaining knowledge in Scala and most importantly practical examples of Spark applications. It gave me an understanding of all the relevant Spark core concepts, RDDs, Dataframes & Datasets, Spark Streaming, AWS EMR. Within a few months of completion, I used the knowledge gained from the course to propose in my current company to work primarily on Spark applications. Since then I have continued to work with Spark. I would highly recommend any of Franks courses as he simplifies concepts well and his teaching manner is easy to follow and continue with! " - Joey Faherty

    Online self studyIntermediate
    ₹ 9,600 96% OFF ₹ 450 Take this Course

    Big Data, Data Analysis, java, Data Science, Machine Learning

    Offered by:  UDEMY
  8. Big Data Hadoop Expert Program - Online Classroom

    The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. | Mastering Hadoop and related tools: The course provides you with an in-depth understanding of the Hadoop framework including HDFS, YARN, and MapReduce. | Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. | The ‘Impala-an Open Source SQL Engine for Hadoop’ is an ideal course package for individuals who want to understand the basic concepts of Massively Parallel Processing or MPP SQL query engine that runs on Apache Hadoop. On completing this course, learners will be able to interpret the role of Impala in the Big Data Ecosystem. | MongoDB Developer and Administrator certification from Simplilearn would equip you to master the skills to become MongoDB experienced professional. By going through this MongoDB training you would become job ready by mastering data modelling, ingestion, query and Sharding, Data Replication with MongoDB along with installing, updating and maintaining MongoDB environment. | Apache Kafka is an open source Apache project. It is a high-performance real-time messaging system that can process millions of messages per second. It provides a distributed and partitioned messaging system and is highly fault tolerant.

    Offered by:  Simplilearn
  9. Big Data and Hadoop Spark Developer Training

    Big Data has become increasingly popular with the need to analyse large sets of data and big data professionals are in great demand. This course is aimed at providing valuable technical skillsin Big Data and Hadoop for professionals who are seeking real-world experience to deal with big data. This certification course will help learners to be job-ready in the big data industry. With quality online content, this course prepares the candidates with real life projects. The training not only equips the learners with necessary skills in Hadoop but also provides the necessary work experience in the field through real life projects. Candidates can take the advantage of the learning materials and assignments that the course provides.

    13690 Students
    24 Hours Online self studyIntermediate
    ₹ 15,338 15% OFF ₹ 13,037 Enquire Now

    Big Data, java, Machine Learning, Insurance, Operations

    Offered by:  Simplilearn
  10. Hadoop Administrator

    Hadoop is an Apache Software Foundation project and open source software platform for scalable, distributed computing. Hadoop can provide fast and reliable analysis of both structured data and unstructured data. In this course you will learn about the design principles, the cluster architecture, considerations for servers and operating systems, and how to plan for a deployment. This learning path can be used as part of the preparation for the Cloudera Certified Administrator for Apache Hadoop (CCA-500) exam. | Apache Spark Fundamentals course introduces to the various components of the spark framework to efficiently process, visualize and analyze data. The course takes you through spark applications using Python, Scala and Java. You will also learn about the apache spark programming fundamentals like resilient distributed datasets and check which operations to be used to do a transformation operation on the RDD. This will also show you how to save and load data from different data sources like different type of files, RDBMS databases and NO-SQL. At the end of the course, you will explore effective spark application and execute it on Hadoop cluster to make informed business decisions.

    31 HoursOnline self studyIntermediate
    $ 153

    java, Operations

    Offered by:  Skillsoft
  11. Big Data and Hadoop Spark Developer

    Big Data has become increasingly popular with the need to analyse large sets of data and big data professionals are in great demand. This course is aimed at providing valuable technical skillsin Big Data and Hadoop for professionals who are seeking real-world experience to deal with big data. This certification course will help learners to be job-ready in the big data industry. With quality online content, this course prepares the candidates with real life projects. The training not only equips the learners with necessary skills in Hadoop but also provides the necessary work experience in the field through real life projects. Candidates can take the advantage of the learning materials and assignments that the course provides.

    4278 Students
    36 Hours Online ClassroomIntermediate
    $ 408 Enquire Now

    Big Data, java, Machine Learning, Insurance, Operations

    Offered by:  Simplilearn
  12. Apache Spark Advanced Topics

    Spark Core provides basic I/O functionalities, distributed task dispatching, and scheduling. Resilient Distributed Datasets (RDDs) are logical collections of data partitioned across machines. RDDs can be created by referencing datasets in external storage systems, or by applying transformations on existing RDDs. In this course, you will learn how to improve Spark's performance and work with Data Frames and Spark SQL. Spark Streaming leverages Spark's language-integrated API to perform streaming analytics. This design enables the same set of application code written for batch processing to join streams against historical data, or run ad-hoc queries on stream state. In this course, you will learn how to work with different input streams, perform transformations on streams, and tune up performance. MLlib is Spark's machine learning library. GraphX is Spark's API for graphs and graph-parallel computation. SparkR exposes the API and allows users to run jobs from the R shell on a cluster. In this course, you will learn how to work with each of these libraries.

    7 HoursOnline self studyIntermediate
    $ 74

    Machine Learning, Operations

    Offered by:  Skillsoft
  13. Spark and Python for Big Data with PySpark

    Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Python! One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark ! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!Spark can perform up to 100x faster than Hadoop MapReduce , which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market! This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we've done that we'll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way you'll have exercises and Mock Consulting Projects that put you right into a real world situation where you need to use your new skills to solve a real problem! We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30 day money back guarantee and comes with a LinkedIn Certificate of Completion! If you're ready to jump into the world of Python, Spark, and Big Data, this is the course for you!

    Online self studyIntermediate
    ₹ 12,480 97% OFF ₹ 451 Take this Course

    Big Data, Languages, Machine Learning, Data Analysis, Operations

    Offered by:  UDEMY
  14. Apache Kafka for Beginners - Learn Kafka by Hands-On

    Description: Learn the fundamentals and advanced concepts of Apache Kafka in this course. There will be a hands on for each concept using inbuilt shell scripts that are available inside the Kafka download and using Java, Camel,Spark Spring Boot and Docker . This course will walk you through the concepts step by step and immediate hands on for each topic discussed. This course will help increase your technical expertise in Kafka. This course will be an eyeopener for people think Kafka is a complex system, eventually you will understand how simple Kafka is. This course can be a career breakthrough and assure you that you will find yourself in a better place after you complete this course. This course will transfer your from novice Kafka user to a experienced Kafka user. Why I should take this course ? This course will walk you through the Kafka architecture, different components of the Kafka architecture and advantages of Kafka over other systems. This course will focus on the internals of the Kafka and how to use Kafka and implement the concepts that are learnt in real time. This course will teach you how to implement the concepts using Java, Camel, Spark, Spring Boot and Docker. Course Overview: Section 1: Getting Started This section explains about the author and the course objectives. Section 2: Kafka Architecture This section explains about the following: Why do you need Kafka ? What is Kafka ? Kafka Architecture and the different components in the Kafka architecture. Role of zookeeper, Kafka Broker, Kafka Cluster, Producers and Consumers. Section 3: Download Kafka This sections explored about the different approaches of downloading the Kafka distribution in your local. Section 4: Core Internals of Apache Kafka + Hands on This section shows you the demo on how to start zookeeper and Kafka broker. Detailed explanation about Topics, Partitions, Consumers and Producers. Hands on creating topic and how to connect producer and consumers to the created topic using Console Producer and Consumer . Hands on about Kafka commit log. Section 5 : Kafka API's This section explains about the different Core API's and its use cases. Section 6 : Behind the scenes zookeeper, Broker , Producer and Consumers This section explains about what are the different Kafka components that interact with each to create a topic using a flow diagram . This sections also covers how producers and consumers connect to the Kafka and what are the different components that interact with each other behind the scenes. Section 7 : Running Multiple Brokers Hands on how to run multiple brokers in your machine. How does the consumer and producer while running it against the multiple brokers. Hands on Leader, Replica and ISR attributes in a Topic. Section 8 : Kafka Producers Detailed explanation about Kafka Producer and how to connect to the Kafka Cluster. How to implement the Kafka producer using Java? Exploring different partitioning mechanism and implementation in Java. How to alter the configuration of a topic ? Section 9 : Kafka Consumer Detailed explanation about Kafka Consumer. How to implement the Kafka Consumer using Java? Different types of Offset Management in Kafka Consumer. Automatic Offset Management using Java. Manual Offset Management using Java. Consumer Groups in Kafka consumer and its Advantages. Consumer Group id and its benefits. Implementation of consumer group in Java. How to reset the offset to a particular value in Kafka Consumer ? Section 10: Kafka Client - GUI Tool In this section we will download, install and demo about the Kafka GUI client tool that will be used to connect and Manage the Kafka cluster. Section 11: Apache Camel + Kafka Integrationa Quick Introduction to Apache Camel Apache Camel simple example Apache Camel Architecture Hands on - How to Build a Kafka consumer using Apache Camel Framework ? Hands on - How to Build a Kafka producer using Apache Camel Framework ? Section 12: Apache Spark + Kafka Integrationa Quick Introduction to Apache Spark Hands on - How to Build a Kafka consumer using Apache Spark Framework ? Section 12: Additional Configurations How to delete a topic ? Section 13: Apache Kafka -Spring Boot Implementation This section explains about the Spring boot Implementation of Apache Kafka modules Quick Introduction to Spring Quick Introduction to Spring boot Simple Spring Boot App via hands on Kafka Consumer using Spring Boot Kafka Producer using Spring Boot Section 14: Docker - Dockerize Kafka Broker, Zookeeper, Producer and Consumer In this section we will run the dockerized version of kafka broker, zookeeper and we will create the docker image of the Spring boot App. Quick Introduction to Docker. Installation of Docker Tool Box on Windows 10. Installation of Docker Tool Box on Mac. Creating a docker image of the spring boot App Creating an Account in Docker Hub and push/pull from Docker Hub. Exploring Different Docker commands. How to run Kafka Broker/Zookeeper in Docker ? Complete Integration and working app of Dockerized Kafka Broker, Zookeeper and dockerized Spring boot app. Section 15: Apache Kafka Security and Authentication In this section we will explore about the Kafka security Why do you need Kafka security ? Hands on session on how to enable SSL in Kafka Broker ? Hands on session on how to access the SSL secured broker using Console Consumer/Producer ? Hands on session on how to configure SSL in Kafka Producer using Java ? Hands on Session on how to configure SSL in Kafka Consumer using Java ? How to delete a topic ? Section 16: Conclusion Congratulations and Thank You ! By the end of this you will have a complete understanding of how Apache Kafka works and how to implement the concepts in real time using Java, Apache Camel, Apache Spark , Spring Boot and Docker.

    Online self studyIntermediate
    ₹ 2,560 83% OFF ₹ 450 Take this Course

    java

    Offered by:  UDEMY
  15. Big Data Hadoop & Spark Developer

    Spark Core provides basic I/O functionalities, distributed task dispatching, and scheduling. Resilient Distributed Datasets (RDDs) are logical collections of data partitioned across machines. RDDs can be created by referencing datasets in external storage systems, or by applying transformations on existing RDDs. In this course, you will learn how to improve Spark's performance and work with Data Frames and Spark SQL. Spark Streaming leverages Spark's language-integrated API to perform streaming analytics. This design enables the same set of application code written for batch processing to join streams against historical data, or run ad-hoc queries on stream state. In this course, you will learn how to work with different input streams, perform transformations on streams, and tune up performance. MLlib is Spark's machine learning library. GraphX is Spark's API for graphs and graph-parallel computation. SparkR exposes the API and allows users to run jobs from the R shell on a cluster. In this course, you will learn how to work with each of these libraries.

    26 HoursOnline self studyIntermediate
    $ 218

    Machine Learning, Big Data, Big Data & Hadoop, Operations

    Offered by:  Skillsoft
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