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Python Spark Certification Training using PySpark ( L067 )

4.5 + (25,859) Students Ratings

By taking this Python Spark Certification Training using PySpark from IQ Online helps you to gain the skills and knowledge that are required to become a successful Spark Developer using Python and it makes you ready for the Cloudera Hadoop and Spark Developer Certification Exam (CCA175). By taking this course, you will get an in-depth knowledge of Apache Spark and Spark Ecosystem, which includes Spark RDD, Spark SQL, Spark MLlib and Spark Streaming. Also, gain the complete knowledge of Python Programming language, HDFS, Sqoop, Flume, Spark GraphX and Messaging System such as Kafka.

Course Price :

₹22,765
₹25,294
10%
off
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Live Instructor

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Live Online Classes

All our Classes are Live Instrucotor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schdules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of Completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Training Schedule
Batch Start Date Days of Training Weekday/ Weekend Timings
28-Mar-2020 Available SAT & SUN (6 WEEKS) Weekend Batch 11:00 AM - 02:00 PM (EST)
17-Apr-2020 Available SAT & SUN (6 WEEKS) Weekend Batch 09:30 PM - 12:30 AM (EST)
 
 
 
 
 

Course Curriculum

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

 

Topics:

  • Introduction of Big Data
  • What are Big Data Customer Scenarios
  • What are the limitations and solutions of existing Data Analytics Architecture with Uber Use Case
  • Understand how Hadoop Solves the Big Data Problem?
  • Define Hadoop
  • Key Characteristics of Hadoop
  • Describe the Hadoop Ecosystem and HDFS
  • Understand about the Hadoop Core Components
  • Learn about Rack Awareness and Block Replication
  • Define YARN and the advantage of YARN
  • Discuss Hadoop Cluster and its Architecture
  • Know about the Hadoop: Different Cluster Modes
  • Understand about Big Data Analytics with Batch & Real-Time Processing
  • Requirement of Spark
  • Define Spark
  • Evaluate the difference between the Spark from its Competitors?
  • Discuss the Spark at eBay
  • Understand the Spark’s Place in the Hadoop Ecosystem

Learning Objectives: This module will help you to understand the basics of Python programming and learn different types of sequence structures, related operations, and their usage. Also, understand the various ways of opening, reading, and writing to files. 

 

Topics:

  • Python Overview
  • What are the different Applications where Python is Used?
  • Discuss Values, Types, Variables
  • Define Operands and Expressions
  • Understand the Conditional Statements
  • Describe Loops
  • Describe the Command Line Arguments
  • About writing to the Screen
  • Discuss Python files I/O Functions
  • Learn about the Numbers
  • Discuss Strings and related operations
  • Discuss Tuples and related operations
  • Discuss Lists and related operations
  • Discuss Dictionaries and related operations
  • Discuss Sets and related operations

 

Hands-On:

  • Learn to create “Hello World” code
  • Understand the Conditional Statements
  • Describe Loops
  • Discuss Tuple - properties, related operations, compared with a list
  • Discuss List - properties, related operations
  • Discuss Dictionary - properties, related operations
  • Discuss Set - properties, related operations

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

Topics:

  • Define Functions
  • What are Function Parameters
  • Describe Global Variables
  • Discuss Variable Scope and Returning Values
  • Define Lambda Functions
  • Learn the Object-Oriented Concepts
  • Understand the Standard Libraries
  • Which Modules Used in Python
  • What are the Import Statements
  • Describe Module Search Path
  • Learn about Package Installation Ways

 Hands-On:

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

Learning Objectives: In this module, you will understand Apache Spark and its components, You will learn how to create and run various spark applications. Besides, you will also learn how to perform data ingestion using Sqoop. 

 

Topics:

  • Introduction of Spark Components and its Architecture
  • Discuss the Spark Deployment Modes
  • PySpark Shell - Introduction
  • Learn how to submit PySpark Job
  • Define Spark Web UI
  • How to write your first PySpark Job using Jupyter Notebook
  • Describe Data Ingestion using Sqoop

 

Hands-On:

  • Learn about Building and Running Spark Application
  • Describe Spark Application Web UI
  • Get to know about different Spark Properties

Learning Objectives: This module will help you to understand the topics such as Spark - RDDs and other RDD related manipulations for implementing business logic (Transformations, Actions, and Functions performed on RDD). 

 

Topics:

  • What are the challenges in Existing Computing Methods
  • Discuss the probable Solution and How RDD Solves the Problem
  • Explain RDD, it’s Operations, Transformations, and Actions
  • Understand the Data Loading and Saving Through RDDs
  • What are the Key-Value Pair RDDs
  • Describe Other Pair RDDs, Two Pair RDDs
  • Define RDD Lineage
  • Define RDD Persistence
  • Learn the WordCount Program Using RDD Concepts
  • Explain the RDD Partitioning and How it helps achieve Parallelization
  • Learn how to pass Functions to Spark

 

Hands-On:

  • Understand the loading data in RDDs
  • Understand saving data through RDDs
  • Explanation on RDD Transformations
  • Describe RDD Actions and Functions
  • Define RDD Partitions
  • Learn WordCount through RDDs

Learning Objectives: This module will help you to learn about SparkSQL which is used to process structured data with SQL queries. About data-frames and datasets in Spark SQL along with different kinds of SQL operations performed on the data-frames. Also, learn about Spark and Hive integration.  

Topics:

  • About Spark SQL
  • Spark SQL - Introduction
  • The Architecture of Spark SQL
  • Explain SQLContext in Spark SQL
  • Define Schema RDDs
  • What are User Defined Functions
  • Discuss Data Frames & Datasets
  • Explain Interoperating with RDDs
  • Learn JSON and Parquet File Formats
  • Understand the loading Data through Different Sources
  • Describe Spark-Hive Integration

Hands-On:

  • Explain Spark SQL - Creating data frames
  • Understand the loading and transforming data through different sources
  • Brief Stock Market Analysis
  • Describe Spark-Hive Integration

Learning Objectives: This module will help you to know about why machine learning is needed, different Machine Learning techniques/algorithms and their implementation using Spark MLlib.

Topics:

  • Need for Machine Learning
  • Machine Learning - Introduction
  • Understand where Machine Learning is used
  • Discuss Face Detection: USE CASE
  • What are the various different types of Machine Learning Techniques
  • MLlib - Introduction
  • Learn about the features of MLlib and MLlib Tools
  • Which are the various ML algorithms supported by MLlib

Learning Objectives: This module will help you to understand how to implement various algorithms supported by MLlib such as Linear Regression, Decision Tree, Random Forest and many more. 

Topics:

  • Get supervised learning algorithms such as Linear Regression, Logistic Regression, Decision Tree, Random Forest
  • Get unsupervised learning about the K-Means Clustering and how It Works with MLlib
  • Understand the analysis of US Election Data using MLlib (K-Means)

 Hands-On:

  • Describe K- Means Clustering
  • Define Linear Regression
  • Define Logistic Regression
  • Define Decision Tree
  • Define Random Forest

Learning Objectives: This module will help you to understand about Kafka and Kafka Architecture. Later get to know the details of Kafka Cluster and you will also learn how to configure different types of Kafka Cluster. Know how messages are produced and consumed using Kafka API’s in Java. Also, get introduced to Apache Flume, its basic architecture and how it is integrated with Apache Kafka for event processing. And also know how to ingest streaming data using flume. 

Topics:

  • Requirement for Kafka
  • Introduction - Kafka
  • Learn the core concepts of Kafka
  • Describe Kafka Architecture
  • Understand where is Kafka used
  • Know the Components of Kafka Cluster
  • Learn how to configure Kafka Cluster
  • Discuss Kafka Producer and Consumer Java API
  • The requirement of Apache Flume
  • Introduction - Apache Flume
  • Describe basic Flume Architecture
  • Explain Flume Sources
  • Explain Flume Sinks
  • Explain Flume Channels
  • Explain Flume Configuration
  • Know about the integrating Apache Flume and Apache Kafka

Hands-On:

  • Learn how to configure Single Node Single Broker Cluster
  • Learn how to configure Single Node Multi-Broker Cluster
  • Discuss producing and consuming messages through Kafka Java API
  • Understand the Flume Commands
  • How to set up Flume Agent
  • How to stream Twitter Data into HDFS

Learning Objectives: This module will help you to learn Spark streaming which is used to build scalable fault-tolerant streaming applications. Know how the DStreams and various Transformations performed on the streaming data. Also, commonly used streaming operators such as Sliding Window Operators and Stateful Operators. 

Topics:

  • Existing Computing Methods - Drawbacks
  • Know the streaming necessity
  • Spark Streaming
  • Features of Spark Streaming
  • Understand the Spark Streaming Workflow
  • Learn how Uber Uses Streaming Data
  • Discuss Streaming Context and DStreams
  • Discuss Transformations on DStreams
  • Windowed Operators and Why it is Useful?
  • What are the important Windowed Operators
  • Define Slice, Window and ReduceByWindow Operators
  • Define Stateful Operators

Hands-On:

  • Understand how the WordCount Program using Spark Streaming works.

Learning Objectives: From this module, you will get to know about the different streaming data sources such as Kafka and flume. Besides, you will be able to create a spark streaming application. 

Topics:

  • Introduction of Apache Spark Streaming - Data Sources
  • Discuss Streaming Data Source Overview
  • Describe the Apache Flume and Apache Kafka Data Sources
  • Give an example using a Kafka Direct Data Source

 Hands-On:

  • Understand the various Spark Streaming Data Sources

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. Also, get to be assured that a population who are underserved 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 the loans are given with a principal, maturity, and also ensure about 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 customer feedback and review. Also, know how to use two different API's (Spark RDD and Spark DataFrame) on datasets to find the best ranking movies.

Learning Objective: This module will help you to understand the key concepts of Spark GraphX programming concepts and operations along with different GraphX algorithms and their implementations. 

Topics:

  • Spark GraphX - Introduction
  • Understand the information about a Graph
  • Discuss the GraphX Basic APIs and Operations
  • Understand the Spark GraphX Algorithm - PageRank, Personalized PageRank, Triangle Count, Shortest Paths, Connected Components, Strongly Connected Components, Label Propagation

Hands-On:

  • Will understand the traveling salesman problem
  • Know about the Minimum Spanning Trees
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Course Details

By taking this Python Spark Certification Training, you will be able to understand:

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

Nowadays Big Data Analytics is having an extreme impact across the world and with such strong growth market demand of this Big Data brings a great opportunity for all IT Professionals. Below is a list of some of the Professional IT groups, who are continuously enjoying the benefits and perks of moving into the 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

There are no prerequisites for this Python Spark Training Course. But, having prior knowledge of Python Programming and SQL will be helpful but is not at all mandatory.

Python Spark Certification Training using PySpark Ceritficate

Python Spark Certification Training using PySpark Reviews

25,859

Total number of reviews

4.5

Aggregate review score

80%

Course completion rate

Python Spark Certification Training using PySpark Features

Live Online Classes

All our Classes are Live Instructor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schedules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Course Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

Python Spark Certification Training using PySpark FAQs

You will never miss a class at IQ Online Training! You can choose either of the two options:

  1. View the recorded session of the class available in your LMS or
  2. You can attend the missed session in any other live batch.

After the enrolment, the LMS access will be instantly provided to you able to access for lifetime which includes complete set of previous class recordings/PPTs/PDFs/assignments. You can start learning right away.

Your access to the Support Team is for lifetime. Our team will help you in resolving queries, during and after the course.

Yes, once enrollment has done for course. Access to the course material will be available for lifetime.

You can Call our support numbers listed in site OR Email us at info@iqtrainings.com.

You can view in-depth class sample recordings before the enrollment. Experience the complete learning instead of a demo session with our expertise.

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

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