CertAchiever

Apache Spark and Scala Certification Training

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Instructor-led live online classes

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Apache Spark and Scala Certification Training

$399

Apache Spark and Scala Certification Training

Apache Spark and Scala certification training is created to help you master Apache Spark and the Spark Ecosystem, which includes Spark RDD, Spark SQL, and Spark MLlib. This Apache Spark training is live, instructor-led & helps you master key Apache Spark concepts, with hands-on demonstrations. This Apache Spark course is fully immersive where you can learn and interact with the instructor and your peers.

Training Features

Instructor-led Sessions

Both Weekdays and Weekend batches are available.

Real-Life Case Studies

During the sessions you will be working on the case studies provided by the trainer.

Lifetime Access

You will get the life time access of training material including videos & study guides..

Assignments

Each class will be followed by practical assignments to practice the concepts covered in class

24 x 7 Expert Support

We have a lifetime 24x7 online support team to resolve all your technical queries,through a ticket based tracking system..

Certification

Towards the end of the course, you will be awarded with Training competition certification based on you performance.

Course Curriculum

Learning Objectives

Understand Big Data and its components such as HDFS. You will learn about the Hadoop Cluster Architecture, Introduction to Spark and the difference between batch processing and real-time processing.

Topics Covered

What is Big Data?, What is Big Data?, Big Data Customer Scenarios, Limitations and Solutions of Existing Data Analytics Architecture with Uber Use Case, How Hadoop Solves the Big Data Problem?, What is Hadoop?, Hadoop’s Key Characteristics, Hadoop Ecosystem and HDFS, Hadoop Core Components, Rack Awareness and Block Replication, YARN and its Advantage, Hadoop Cluster and its Architecture, Hadoop: Different Cluster Modes, Hadoop Terminal Commands, Big Data Analytics with Batch & Real-time Processing, Why Spark is needed?, What is Spark?, How Spark differs from other frameworks?, Spark at Yahoo!

Learning Objectives

Learn the basics of Scala that are required for programming Spark applications. You will also learn about the basic constructs of Scala such as variable types, control structures, collections such as Array, ArrayBuffer, Map, Lists, and many more.

Topics Covered

What is Scala?, What is Scala?, Why Scala for Spark?, Scala in other Frameworks, Introduction to Scala REPL, Basic Scala Operations, Variable Types in Scala, Control Structures in Scala, Foreach loop, Functions and Procedures, Collections in Scala- Array, ArrayBuffer, Map, Tuples, Lists, and more

Hands On

Scala REPL Detailed Demo, Scala REPL Detailed Demo

Learning Objectives

In this module, you will learn about object-oriented programming and functional programming techniques in Scala.

Topics Covered

Functional Programming, Functional Programming, Higher Order Functions, Anonymous Functions, Class in Scala, Getters and Setters, Custom Getters and Setters, Properties with only Getters, Auxiliary Constructor and Primary Constructor, Singletons, Extending a Class, Overriding Methods, Traits as Interfaces and Layered Traits

Hands On

OOPs Concepts Functional Programming, OOPs Concepts Functional Programming, Functional Programming

Learning Objectives

Understand Apache Spark and learn how to develop Spark applications. At the end, you will learn how to perform data ingestion using Sqoop.

Topics Covered

Spark’s Place in Hadoop Ecosystem, Spark’s Place in Hadoop Ecosystem, Spark Components & its Architecture, Spark Deployment Modes, Introduction to Spark Shell, Writing your first Spark Job Using SBT, Submitting Spark Job, Spark Web UI, Data Ingestion using Sqoop

Hands On

Building and Running Spark Application Spark Application Web UI Configuring Spark Properties Data ingestion using Sqoop, Building and Running Spark Application Spark Application Web UI Configuring Spark Properties Data ingestion using Sqoop, Spark Application Web UI Configuring Spark Properties Data ingestion using Sqoop, Configuring Spark Properties Data ingestion using Sqoop, Data ingestion using Sqoop

Learning Objectives

Get an insight of Spark - RDDs and other RDD related manipulations for implementing business logics (Transformations, Actions, and Functions performed on RDD).

Topics Covered

Challenges in Existing Computing Methods, Challenges in Existing Computing Methods, Probable Solution & How RDD Solves the Problem, What is RDD, It’s Operations, Transformations & Actions, Data Loading and Saving Through RDDs, Key-Value Pair RDDs, Other Pair RDDs, Two Pair RDDs, RDD Lineage, RDD Persistence, WordCount Program Using RDD Concepts, RDD Partitioning & How It Helps Achieve Parallelization, Passing Functions to Spark

Hands On

Loading data in RDDs Saving data through RDDs RDD Transformations RDD Actions and Functions RDD Partitions WordCount through RDDs, Loading data in RDDs Saving data through RDDs RDD Transformations RDD Actions and Functions RDD Partitions WordCount through RDDs, Saving data through RDDs RDD Transformations RDD Actions and Functions RDD Partitions WordCount through RDDs, RDD Transformations RDD Actions and Functions RDD Partitions WordCount through RDDs, RDD Actions and Functions RDD Partitions WordCount through RDDs, RDD Partitions WordCount through RDDs, WordCount through RDDs

Learning Objectives

In this module, you will learn about SparkSQL which is used to process structured data with SQL queries, data-frames and datasets in Spark SQL along with different kind of SQL operations performed on the data-frames. You will also learn about Spark and Hive integration.

Topics Covered

Need for Spark SQL, Need for Spark SQL, What is Spark SQL?, Spark SQL Architecture, SQL Context in Spark SQL, User Defined Functions, Data Frames & Datasets, Interoperating with RDDs, JSON and Parquet File Formats, Loading Data through Different Sources, Spark – Hive Integration

Hands On

Spark SQL – Creating Data Frames Loading and Transforming Data through Different Sources Stock Market Analysis Spark-Hive Integration, Spark SQL – Creating Data Frames Loading and Transforming Data through Different Sources Stock Market Analysis Spark-Hive Integration, Loading and Transforming Data through Different Sources Stock Market Analysis Spark-Hive Integration, Stock Market Analysis Spark-Hive Integration, Spark-Hive Integration

Learning Objectives

Learn why machine learning is needed, different Machine Learning techniques/algorithms, and SparK MLlib.

Topics Covered

Why Machine Learning?, Why Machine Learning?, What is Machine Learning?, Where Machine Learning is Used?, Face Detection: USE CASE, Different Types of Machine Learning Techniques, Introduction to MLlib, Features of MLlib and MLlib Tools, Various ML algorithms supported by MLlib

Learning Objectives

Implement various algorithms supported by MLlib such as Linear Regression, Decision Tree, Random Forest and many more.

Topics Covered

Supervised Learning - Linear Regression, Logistic Regression, Decision Tree, Random Forest, Supervised Learning - Linear Regression, Logistic Regression, Decision Tree, Random Forest, Unsupervised Learning - K-Means Clustering & How It Works with MLlib, Analysis on US Election Data using MLlib (K-Means)

Hands On

Machine Learning MLlib K- Means Clustering Linear Regression Logistic Regression Decision Tree Random Forest, Machine Learning MLlib K- Means Clustering Linear Regression Logistic Regression Decision Tree Random Forest, K- Means Clustering Linear Regression Logistic Regression Decision Tree Random Forest, Linear Regression Logistic Regression Decision Tree Random Forest, Logistic Regression Decision Tree Random Forest, Decision Tree Random Forest, Random Forest

Learning Objectives

Understand Kafka and its Architecture. Also, learn about Kafka Cluster, how to configure different types of Kafka Cluster. Get introduced to Apache Flume, its architecture and how it is integrated with Apache Kafka for event processing. In the end, learn how to ingest streaming data using flume.

Topics Covered

Need for Kafka, Need for Kafka, What is Kafka?, Core Concepts of Kafka, Kafka Architecture, Where is Kafka Used?, Understanding the Components of Kafka Cluster, Configuring Kafka Cluster, Kafka Producer and Consumer Java API, Need of Apache Flume, What is Apache Flume?, Basic Flume Architecture, Flume Sources, Flume Sinks, Flume Channels, Flume Configuration, Integrating Apache Flume and Apache Kafka

Hands On

Configuring Single Node Single Broker Cluster Configuring Single Node Multi Broker Cluster Producing and consuming messages Flume Commands Setting up Flume Agent Streaming Twitter Data into HDFS, Configuring Single Node Single Broker Cluster Configuring Single Node Multi Broker Cluster Producing and consuming messages Flume Commands Setting up Flume Agent Streaming Twitter Data into HDFS, Configuring Single Node Multi Broker Cluster Producing and consuming messages Flume Commands Setting up Flume Agent Streaming Twitter Data into HDFS, Producing and consuming messages Flume Commands Setting up Flume Agent Streaming Twitter Data into HDFS, Flume Commands Setting up Flume Agent Streaming Twitter Data into HDFS, Setting up Flume Agent Streaming Twitter Data into HDFS, Streaming Twitter Data into HDFS

Learning Objectives

Work on Spark streaming which is used to build scalable fault-tolerant streaming applications. Also, learn about DStreams and various Transformations performed on the streaming data. You will get to know about commonly used streaming operators such as Sliding Window Operators and Stateful Operators.

Topics Covered

Drawbacks in Existing Computing Methods, Drawbacks in Existing Computing Methods, Why Streaming is Necessary?, What is Spark Streaming?, Spark Streaming Features, Spark Streaming Workflow, How Uber Uses Streaming Data, Streaming Context & DStreams, Transformations on DStreams, Describe Windowed Operators and Why it is Useful, Important Windowed Operators, Slice, Window and ReduceByWindow Operators, Stateful Operators

Learning Objectives

In this module, you will learn about the different streaming data sources such as Kafka and flume. At the end of the module, you will be able to create a spark streaming application.

Topics Covered

Apache Spark Streaming: Data Sources, Apache Spark Streaming: Data Sources, Streaming Data Source Overview, Apache Flume and Apache Kafka Data Sources, Example: Using a Kafka Direct Data Source, Perform Twitter Sentimental Analysis Using Spark Streaming

Hands On

Different Streaming Data Sources, Different Streaming Data Sources

FAQ's

You will never miss a lecture at CertAchiever! You can choose either of the two options:

View the recorded session of the class available in your LMS.

·You can attend the missed session, in any other live batch."

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in the class.

You can give us a CALL at +918882136965 (IN) OR email at admin@certachiever.com

Certification

Once your training will complete, you will be awarded with training completion certification from the Trainer.