PySpark Certification Training Course

Theeduplus’s PySpark certification education is curated through pinnacle enterprise specialists to fulfill the enterprise benchmarks. This PySpark path is created that will help you grasp competencies which can be required to emerge as a a success Spark developer the usage of Python. Our PySpark on-line path is live, teacher-led & allows you grasp key PySpark standards with hands-on demonstrations. This PySpark education is completely immersive, in which you could research and engage with the teacher and your peers. Enroll now with this path to research from pinnacle-rated instructors.

Why should you take PySpark course?

Apache Spark will dominate the Big Data landscape by 2022 - Wikibon
As per Indeed.com, the average salary for Spark Developer is $180,000 per annum.

PySpark Course Curriculum

Introduction to Big Data Hadoop and Spark

Learning Objectives: In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, Hadoop ecosystem components, Hadoop Architecture, HDFS, Rack Awareness, and Replication. You will learn about the Hadoop Cluster Architecture, important configuration files in a Hadoop Cluster. You will also get an introduction to Spark, why it is used and understanding of the difference between batch processing and real-time processing.

Topics:

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
Big Data Analytics with Batch & Real-Time Processing
Why Spark is Needed?
What is Spark?
How Spark Differs from its Competitors?
Spark at eBay
Spark’s Place in Hadoop Ecosystem

Introduction to Python for Apache Spark

Learning Objectives: In this module, you will learn basics of Python programming and learn different types of sequence structures, related operations and their usage. You will also learn diverse ways of opening, reading, and writing to files.

Topics:

Overview of Python
Different Applications where Python is Used
Values, Types, Variables
Operands and Expressions
Conditional Statements
Loops
Command Line Arguments
Writing to the Screen
Python files I/O Functions
Numbers
Strings and related operations
Tuples and related operations
Lists and related operations
Dictionaries and related operations
Sets and related operations

Hands-On:

Creating “Hello World” code
Demonstrating Conditional Statements
Demonstrating Loops
Tuple - properties, related operations, compared with list
List - properties, related operations
Dictionary - properties, related operations
Set - properties, related operations

Functions, OOPs, and Modules in Python

Learning Objectives: In this Module, you will learn how to create generic python scripts, how to address errors/exceptions in code and finally how to extract/filter content using regex.

Topics:

Functions
Function Parameters
Global Variables
Variable Scope and Returning Values
Lambda Functions
Object-Oriented Concepts
Standard Libraries
Modules Used in Python
The Import Statements
Module Search Path
Package Installation Ways

Hands-On:

Functions - Syntax, Arguments, Keyword Arguments, Return Values
Lambda - Features, Syntax, Options, Compared with the Functions
Sorting - Sequences, Dictionaries, Limitations of Sorting
Errors and Exceptions - Types of Issues, Remediation
Packages and Module - Modules, Import Options, sys Path

Deep Dive into Apache Spark Framework

Learning Objectives: In this module, you will understand Apache Spark in depth and you will be learning about various Spark components, you will be creating and running various spark applications. At the end, you will learn how to perform data ingestion using Sqoop.

Topics:

Spark Components & its Architecture
Spark Deployment Modes
Introduction to PySpark Shell
Submitting PySpark Job
Spark Web UI
Writing your first PySpark Job Using Jupyter Notebook
Data Ingestion using Sqoop

Hands-On:

Building and Running Spark Application
Spark Application Web UI
Understanding different Spark Properties

Playing with Spark RDDs

Learning Objectives: In this module, you will learn about Spark - RDDs and other RDD related manipulations for implementing business logics (Transformations, Actions, and Functions performed on RDD).

Topics:

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

DataFrames and Spark SQL

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

Topics:

Need for Spark SQL
What is Spark SQL
Spark SQL Architecture
SQL Context in Spark SQL
Schema RDDs
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

Machine Learning using Spark MLlib

Learning Objectives: In this module, you will learn about why machine learning is needed, different Machine Learning techniques/algorithms and their implementation using Spark MLlib.

Topics:

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

Deep Dive into Spark MLlib

Learning Objectives: In this module, you will be implementing various algorithms supported by MLlib such as Linear Regression, Decision Tree, Random Forest and many more.

Topics:

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

Hands-On:

K- Means Clustering
Linear Regression
Logistic Regression
Decision Tree
Random Forest

Understanding Apache Kafka and Apache Flume

Learning Objectives: In this module, you will understand Kafka and Kafka Architecture. Afterward, you will go through the details of Kafka Cluster and you will also learn how to configure different types of Kafka Cluster. After that you will see how messages are produced and consumed using Kafka API’s in Java. You will also get an introduction to Apache Flume, its basic architecture and how it is integrated with Apache Kafka for event processing. You will learn how to ingest streaming data using flume.

Topics:

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 through Kafka Java API
Flume Commands
Setting up Flume Agent
Streaming Twitter Data into HDFS

Apache Spark Streaming - Processing Multiple Batches

Learning Objectives: In this module, you will work on Spark streaming which is used to build scalable fault-tolerant streaming applications. You will 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:

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

Hands-On:

WordCount Program using Spark Streaming

Apache Spark Streaming - Data Sources

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:

Apache Spark Streaming: Data Sources
Streaming Data Source Overview
Apache Flume and Apache Kafka Data Sources
Example: Using a Kafka Direct Data Source

Hands-On:

Various Spark Streaming Data Sources

Implementing an End-to-End Project

Project 1-

Domain: Finance Statement:

A leading financial bank is trying to broaden the financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, it makes use of a variety of alternative data--including telco and transactional information--to predict their clients' repayment abilities. The bank has asked you to develop a solution to ensure that clients capable of repayment are not rejected and that loans are given with a principal, maturity, and repayment calendar that will empower their clients to be successful.

Project 2-

Domain: Media and Entertainment Statement:

Analyze and deduce the best performing movies based on the customer feedback and review. Use two different API's (Spark RDD and Spark Data Frame) on datasets to find the best ranking movies.

Spark GraphX (Self-Paced)

Learning Objective: In this module, you will be learning the key concepts of Spark GraphX programming concepts and operations along with different GraphX algorithms and their implementations.

Topics:

Introduction to Spark GraphX
Information about a Graph
GraphX Basic APIs and Operations
Spark GraphX Algorithm - PageRank, Personalized PageRank, Triangle Count, Shortest Paths, Connected Components, Strongly Connected Components, Label Propagation

Hands-On:

The Traveling Salesman problem
Minimum Spanning Trees

PySpark Certification Course Description

About the PySpark Online Course

Python Spark Certification Training Course is designed to offer you with the expertise and competencies to grow to be a a success Big Data & Spark Developer. This Training could assist you to clean the CCA Spark and Hadoop Developer (CCA175) Examination. You will apprehend the fundamentals of Big Data and Hadoop. You will find out how Spark allows in-reminiscence facts processing and runs a lot quicker than Hadoop MapReduce. You can even find out about RDDs, Spark SQL for dependent processing, distinctive APIs supplied via way of means of Spark which include Spark Streaming, Spark MLlib. This path is an quintessential a part of a Big Data Developer’s Career path. It can even embody the essential ideas which include facts taking pictures the use of Flume, facts loading the use of Sqoop, a messaging machine like Kafka, etc.

What are the objectives of our online PySpark training?

Spark Certification Training is designed by industry experts to make you a Certified Spark Developer. The PySpark Course offers:

Overview of Big Data & Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator)
Comprehensive knowledge of various tools that falls in Spark Ecosystem like Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming
The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
The power of handling real-time data feeds through a publish-subscribe messaging system like Kafka
The exposure to many real-life industry-based projects which will be executed using theeduplus CloudLab
Projects which are diverse in nature covering banking, telecommunication, social media, and government domains
Rigorous involvement of an SME throughout the Spark Training to learn industry standards and best practices

Why should you go for PySpark training online?

Spark is one of the maximum developing and broadly used gear for Big Data & Analytics. It has been followed through a couple of agencies falling into numerous domain names around the world and therefore, gives promising profession opportunities. In order to participate in those styles of opportunities, you want a dependent education this is aligned as according to Cloudera Hadoop and Spark Developer Certification (CCA175) and present day enterprise necessities and first-rate practices. Besides robust theoretical understanding, it's miles pretty vital to have a robust hands-on experience. Hence, throughout theeduplus PySpark course, you may be running on numerous enterprise-primarily based totally use-instances and initiatives incorporating huge information and spark gear as part of the answer strategy. Additionally, all of your doubts could be addressed through the enterprise professional, presently running on real-lifestyles huge information and analytics initiatives

What are the skills that you will be learning with our PySpark Certification Training?

Theeduplus PySpark Training is curated by Industry experts and helps you to become a Spark developer. During this course, you will be trained by Industry practitioners having multiple years of experience in the same domain. During Apache Spark and Scala course, you will be trained by our expert instructors to:

Master the concepts of HDFS
Understand Hadoop 2.x Architecture
Learn data loading techniques using Sqoop
Understand Spark and its Ecosystem
Implement Spark operations on Spark Shell
Understand the role of Spark RDD
Work with RDD in Spark
Implement Spark applications on YARN (Hadoop)
Implement machine learning algorithms like clustering using Spark MLlib API
Understand Spark SQL and it’s architecture
Understand messaging system like Kafka and its components
Integrate Kafka with real time streaming systems like Flume
Use Kafka to produce and consume messages from various sources including real time streaming sources like Twitter
Learn Spark Streaming
Use Spark Streaming for stream processing of live data
Solve multiple real-life industry-based use-cases which will be executed using Theeduplus CloudLab

Who should go for our PySpark Course?

Market for Big Data Analytics is growing tremendously across the world and such strong growth pattern followed by market demand is a great opportunity for all IT Professionals. Here are a few Professional IT groups, who are continuously enjoying the benefits and perks of moving into Big Data domain.

Developers and Architects
BI /ETL/DW Professionals
Senior IT Professionals
Mainframe Professionals
Freshers
Big Data Architects, Engineers and Developers
Data Scientists and Analytics Professionals

How will PySpark online training help your career?

The stats provided below will provide you a glimpse of growing popularity and adoption rate of Big Data tools like Spark in the current as well as upcoming years:

56% of Enterprises Will Increase Their Investment in Big Data over the Next Three Years – Forbes
McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts
Average Salary of Spark Developers is $113k
According to a McKinsey report, US alone will deal with shortage of nearly 190,000 data scientists and 1.5 million data analysts and Big Data managers by 2018

As you know, nowadays, many organizations are showing interest in Big Data and are adopting Spark as a part of solution strategy, the demand of jobs in Big Data and Spark is rising rapidly. So, it is high time to pursue your career in the field of Big Data & Analytics with our best PySpark Course.

What are the pre-requisites for Theeduplus's PySpark Online Course?

There are no such prerequisites for Theeduplus PySpark Training Course. However, prior knowledge of Python Programming and SQL will be helpful but is not at all mandatory.

Python Spark Training FAQ's

What is PySpark?

Apache Spark is an open-source real-time in-memory cluster processing framework. It is used in streaming analytics systems such as bank fraud detection system, recommendation system, etc. Whereas Python is a general-purpose, high-level programming language. It has a wide-range of libraries which supports diverse types of applications. PySpark is a combination of Python and Spark. It provides Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.

What if I have queries after I complete this PySpark course?

Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.

What if I miss a live class of PySpark training?

"You will never miss a lecture at theeduplus 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."

Will I get placement assistance after completing this PySpark certification course?

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

Is the course material accessible to the students even after the PySpark certification training is over?

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

Can I attend a demo session before enrolling in this best PySpark Course?

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 into how are the classes conducted, quality of instructors and the level of interaction in a class.

Who are the instructors for this PySpark online training?

All the instructors at theeduplus are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by theeduplus for providing an awesome learning experience to the participants.

What is RDD in PySpark?

RDD stands for Resilient Distributed Dataset which is the building block of Apache Spark. RDD is fundamental data structure of Apache Spark which is an immutable distributed collection of objects. Each dataset in RDD is divided into logical partitions, which may be computed on different nodes of the cluster.

Is PySpark a language?

PySpark is not a language. PySpark is Python API for Apache Spark using which Python developers can leverage the power of Apache Spark and create in-memory processing applications. PySpark is developed to cater the huge amount of Python community.

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PySpark Certification Training Course