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PySpark Certification Training Course
PySpark Certification Training Course
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Instructor-led Python Spark Certification Training using PySpark live online Training Schedule
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Why enroll for PySpark course?
PySpark Certification Training Benefits
There are several industries making significant investments in big data analytics, including banking, retail, manufacturing, finance, healthcare, and government to make more informed business decisions. That translates into a range of jobs being created within each sector, for which individuals with this expertise will be needed. It is also being forecasted that the rise in demand for these roles far outweighs the current supply. PySpark certification will certainly enhance your chance of landing a good job with handsome salary.
Annual Salary
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Want to become a Big Data Engineer?
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Why PySpark course from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
About your PySpark course
Skills Covered
- Storing Big Data in HDFS
- Transformations and Actions in Spark
- Data Ingestion using Sqoop and Flume
- Querying Big Data using Spark SQL
- Building Data Pipeline using Kafka
- Real-time Data Processing with Spark
Tools Covered
PySpark Certification Training Course Curriculum
Curriculum Designed by Experts
Introduction to Big Data Hadoop and Spark
18 Topics
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
Hands-On
- Hadoop terminal commands
Skills You Will Learn
- Hadoop components and its architecture
- Storing data in HDFS
- Working with HDFS commands
Introduction to Python for Apache Spark
15 Topics
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
Skills You Will Learn
- Writing Python Programs
- Implementing Collections in Python
Functions, OOPs, and Modules in Python
11 Topics
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
Skills You Will Learn
- Implementing OOPs Concepts
- Functional Programming
Deep Dive into Apache Spark Framework
7 Topics
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
Skills You Will Learn
- Writing basic Spark application
- Spark architecture and its components
- Ingesting structured data into HDFS
Playing with Spark RDDs
11 Topics
Topics
- Challenges in Existing Computing Methods
- Probable Solution & How RDD Solves the Problem
- What is RDD, Its 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
Skills You Will Learn
- Transformations and actions in Spark
- Implementing RDDs in Spark
DataFrames and Spark SQL
11 Topics
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
Skills You Will Learn
- Working with DataFrame API
- Querying structured data using Spark SQL
- Integrating Spark with Hive
Machine Learning using Spark MLlib
8 Topics
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
Hands-On
- Face detection use case
Skills You Will Learn
- Understanding machine learning
- Functions and features of MLlib
Deep Dive into Spark MLlib
3 Topics
Topics
- 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
Skills You Will Learn
- Working with machine learning algorithms
- Implementing Spark MLlib
Understanding Apache Kafka and Apache Flume
16 Topics
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
- Flume Commands
- Setting up Flume Agent
- Streaming Twitter Data into HDFS
Skills You Will Learn
- Ingesting unstructured data into HDFS
- Working with Kafka command line tools
Apache Spark Streaming - Processing Multiple Batches
12 Topics
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
Skills You Will Learn
- Working with DStream API
Apache Spark Streaming - Data Sources
4 Topics
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
Skills You Will Learn
- Real-time data processing
- Building data pipelines
Implementing an End-to-End Project
2 Topics
Topics
- Project 1- Domain: Finance
- Project 2- Domain: Media and Entertainment
Hands-On
- Implementing an End-to-End Project
Skills You Will Learn
- Building a data pipeline
Spark GraphX (Self-paced)
4 Topics
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
Skills You Will Learn
- Spark GraphX programming concepts and operations
- Implementing GraphX algorithms
Free Career Counselling
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PySpark Certification Course Description
About the PySpark Online Course
The Python Spark Certification Training Course is designed to provide you with the knowledge and skills to become a successful Big Data & Spark Developer. This training will help you clear the CCA Spark and Hadoop Developer (CCA175) Examination. You will understand the basics of Big Data and Hadoop, along with how Spark enables in-memory data processing and runs much faster than Hadoop MapReduce. This course also covers RDDs, Spark SQL for structured processing, and different APIs offered by Spark, such as Spark Streaming and Spark MLlib. The PySpark online course is an integral part of a Big Data Developer’s career path. It will also encompass fundamental concepts such as data capturing using Flume, data loading using Sqoop, and messaging systems like Kafka, etc.
What are the prerequisites for Edureka's PySpark Online Course?
There are no specific prerequisites for our PySpark Certification Training. However, prior knowledge of Python Programming and SQL will be helpful but is not mandatory.
What are the objectives of our Online PySpark Training Course?
The Spark Certification Training is designed by industry experts to make you a Certified Spark Developer. The PySpark Course offers:
- An overview of Big Data & Hadoop, including HDFS (Hadoop Distributed File System) and YARN (Yet Another Resource Negotiator).
- Comprehensive knowledge of various tools that fall in the Spark Ecosystem, such as 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 to handle real-time data feeds through a publish-subscribe messaging system like Kafka.
- Exposure to many real-life industry-based projects that will be executed using Edureka’s CloudLab.
- Projects that are diverse in nature, covering banking, telecommunications, 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 fastest-growing and widely used tools for Big Data & Analytics. It has been adopted by multiple companies in various domains around the globe and, therefore, offers promising career opportunities. To take part in these kinds of opportunities, you need structured training that is aligned with Cloudera Hadoop and Spark Developer Certification (CCA175) and current industry requirements and best practices. Besides strong theoretical understanding, it is essential to have strong hands-on experience. Hence, during Edureka’s PySpark course, you will be working on various industry-based use cases and projects incorporating big data and Spark tools as part of the solution strategy. Additionally, all your doubts will be addressed by industry professionals currently working on real-life big data and analytics projects.
What skills will you learn with our PySpark Certification Training?
Edureka’s PySpark Training is curated by industry experts and helps you become a Spark developer. During this course, our expert instructors will train you to:
- Master the concepts of HDFS
- Understand Hadoop 2.x Architecture
- Understand Spark and its Ecosystem
- Implement Spark operations on Spark Shell
- Implement Spark applications on YARN (Hadoop)
- Write Spark Applications using Spark RDD concepts
- Learn data ingestion using Sqoop
- Perform SQL queries using Spark SQL
- Implement various machine learning algorithms using Spark MLlib API
- Explain Kafka and its components
- Understand Flume and its components
- Integrate Kafka with real-time streaming systems like Flume
- Use Kafka to produce and consume messages
- Use Spark Streaming for stream processing of live data
- Build Spark Streaming Application
- Process Multiple Batches in Spark Streaming
- Implement different streaming data sources
- Solve multiple real-life industry-based use cases which will be executed using Edureka’s CloudLab
Who should take this PySpark Course?
The market for Big Data Analytics is growing tremendously across the world, and the 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 the Big Data domain:
- Developers and Architects
- BI /ETL/DW Professionals
- Senior IT Professionals
- Testing Professionals
- Mainframe Professionals
- Freshers
- Big Data Enthusiasts
- Software Architects, Engineers, and Developers
- Data Scientists and Analytics Professionals
How will Apache PySpark Certification Training help your career?
The statistics provided below will give you a glimpse of the 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
- The 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 2025
As you know, nowadays, many organizations are showing interest in Big Data and are adopting Spark as part of their solution strategy. The demand for 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 PySpark Certification Training Course.
How will I execute the practicals in this PySpark Certification Training?
You will execute all your PySpark Course Assignments/Case Studies in the Cloud LAB environment provided by Edureka. You will access the Cloud LAB via a browser. In case of any doubts, Edureka’s Support Team will be available 24/7 for prompt assistance.
What is CloudLab?
CloudLab is a cloud-based Spark and Hadoop environment that Edureka offers with the PySpark Training Course. It allows you to execute all the in-class demos and work on real-life Spark case studies fluently. This will not only save you from the trouble of installing and maintaining Spark and Python on a virtual machine but will also provide you with an experience of a real big data and Spark production cluster. You can access the Spark Training CloudLab via your browser, which requires minimal hardware configuration. In case you get stuck at any step, our support team is ready to assist 24/7.
What are the system requirements for the PySpark Training Course?
You don't have to worry about the system requirements as you will be executing your practicals on a Cloud LAB, which is a pre-configured environment. This environment already contains all the necessary tools and services required for Edureka's PySpark Training.
PySpark Certification Training Course Projects
Industry: Finance
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 thi....Industry: Transportation
With the spike in pollution levels and the fuel prices, many Bicycle Sharing Programs are running around the world. Bicycle sharing systems are a means of renting bicycles where ....PySpark Certification
To unlock Edureka’s PySpark Training course completion certificate, you must ensure the following:
- Fully participate in this PySpark Certification Training Course.
- Complete the assessments and projects listed.
Big Data is everywhere, and there is an urgent need to collect and preserve the data being generated to avoid missing out on something important. That's why Big Data Analytics is at the forefront of IT and has become crucial for improving business decision-making and gaining a competitive edge. Technology professionals experienced in Analytics are in high demand as organizations seek ways to leverage the power of Big Data. The number of job postings related to Analytics has significantly increased over the last 12 months. This surge is due to the growing number of organizations implementing Analytics and, consequently, seeking Big Data Analytics professionals. Despite the high demand, there is still a large number of unfilled jobs worldwide due to a shortage of required skills. Choosing a career in the field of Big Data and Analytics can be a fantastic career move and could be the role you've been looking for.
Beginners can easily become familiar with PySpark as it is a user-friendly framework. However, to learn its capabilities and functionality, appropriate guidance and a well-structured training path are required. Beginners interested in a career in Big Data Analytics can sign up for our training and earn certificates to demonstrate their expertise in this domain.
PySpark Certification holds global recognition as a popular framework for analyzing and processing real-time data. The demand for PySpark training is on the rise, and there are many profitable employment opportunities in tech organizations, making it the ideal time for candidates to enroll and earn certification. Due to the wide range of job options and prospects, learning PySpark skills and starting work right away is highly recommended.
Our PySpark certification course is designed to develop skills and evaluate candidates' knowledge. PySpark is currently the most advanced technology globally, opening the door to many possibilities for professionals seeking growth in the Big Data Analytics field. After completing this certification, you will have access to a wide range of job opportunities and be prepared for roles such as Big Data Developer, Big Data Engineer, Big Data Analyst, and many more.
Please visit the page which will guide you through the top Apache Spark Interview questions and answers.
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Python Spark Training FAQs
What is PySpark?
PySpark is a combination of Python and Apache Spark. Apache Spark is an open-source real-time in-memory cluster processing framework used in streaming analytics systems like bank fraud detection and recommendation systems. Python, on the other hand, is a general-purpose, high-level programming language with a wide range of libraries supporting diverse applications. PySpark provides a Python API for Spark, allowing you to leverage the simplicity of Python and the power of Apache Spark to handle Big Data.
What if I have queries after completing this PySpark course?
You will have lifetime access to the Support Team, available 24/7. The team will assist you in resolving queries during and after the course.
What if I miss a live class of PySpark training?
"At Edureka, you will never miss a lecture. You have two options::
- View the recorded session of the class available in your LMS.
- Attend the missed session in any other live batch."
Will I receive placement assistance after completing this PySpark certification course?
- To assist you in your job search, we have included a resume builder tool in your LMS. This tool enables you to create a winning resume in just three easy steps. You will have unlimited access to various templates suitable for different roles and designations. Simply log in to your LMS and click on the "create your resume" option.
Is the course material accessible to students even after completing the PySpark certification training?
Yes, you will have lifetime access to the course material once you have enrolled in the course.
Can I attend a demo session before enrolling in this Best PySpark Course?
- To maintain quality standards, we have a limited number of participants in each live session. Therefore, it is not possible to participate in a live class without enrollment. However, you can go through the sample class recording, which will give you a clear insight into how the classes are conducted, the quality of instructors, and the level of interaction in a class.
Who are the instructors for this PySpark online training?
- All the instructors at Edureka are practitioners from the industry with a minimum of 10-12 years of relevant IT experience. They are subject matter experts and have been trained by Edureka to provide an excellent learning experience to the participants.
What if I have more queries related to this PySpark online course?
- You can contact us via phone at +91 88808 62004/1800 275 9730 (US Toll-free Number) or email us at sales@edureka.co .
What is RDD in PySpark?
RDD stands for Resilient Distributed Dataset, which is the building block of Apache Spark. RDD is a fundamental data structure in Apache Spark, representing an immutable distributed collection of objects. Each dataset in RDD is divided into logical partitions, which can be computed on different nodes of the cluster.
Is PySpark a language?
PySpark is not a language itself. PySpark is the Python API for Apache Spark, which allows Python developers to harness the power of Apache Spark and create in-memory processing applications. PySpark is specifically developed to cater to the large Python community.
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