Big Data and Analytics
Python Spark Certification Training using PySpark
Meticulously curated to cater to the high industry benchmarks, CertOcean’s Pyspark certification training is assiduously designed by top industrial experts. This Python Spark Certification Training using Pyspark is an online course that has been carefully structured to help individuals hone and master skills that are much required to don the hat of a successful Spark developer in today’s age through Python. Our Spark online course, Python Spark Certification Training using PySpark, is instructor-led, live and this helps a learner master the key PySpark concepts with hands-on, practical demonstrations. This PySpark course online is hence completely immersive wherein an individual can learn and interact with his instructor and fellow peers. So, don't hold back and enroll at the earliest in our PySpark course online training.
Why should the learner undertake our Python Spark Certification Training Using Pyspark?
• Apache Spark shall be dominating the limitless Big Data landscape by 2022 as per Wikibon.
• As per Indeed.com, the approximate average salary of a Spark Developer is around $180,000 that he may draw per year.
Learning Aim: In this module of the PySpark course online, the learner would be able to understand Big Data, several limitations of the existing solutions for problems pertaining to Big Data, also how Hadoop helps solve the Big Data problem, the labyrinth Hadoop ecosystem components, along with Hadoop Architecture, Rack Awareness, HDFS and Replication. The learner would be taught about the intricate Hadoop Cluster Architecture; and the supremely important configuration files in a Hadoop Cluster. The learner would also get a lucid overview to Spark, why it is used, and an understanding of the differences between real-time processing and batch processing.
• Big Data Customer Scenarios
• What is Big Data?
• All the Limitations and Solutions of the Existing Data Analytics Architecture with Uber Use Case
• How Hadoop Solves the Big Data Problem?
• What is Hadoop?
• Hadoop Core Components
• Hadoop’s Key Characteristics
• Hadoop Ecosystem and HDFS
• The Big Data Analytics with Batch and also Real-Time Processing
• Rack Awareness and Block Replication
• YARN and its Advantage
• Hadoop Cluster and its Architecture
• Hadoop: Different Cluster Modes
• What is Spark?
• Why Spark is Needed?
• How Spark Differs from its Competitors?
• Spark’s Place in Hadoop Ecosystem
• Spark at eBay
Learning Aim: In this module of the Python Spark Certification Training using PySpark, the learner shall learn the basics of Python programming and he would be taught different types of sequence structures along with the related operations and their varied usages. The learner shall also learn the several diverse ways of reading, opening and writing the files.
• Overview of Python
• Sets and related operations
• Different Applications where Python is Used
• Dictionaries and related operations
• Values, Types, Variables
• Operands and Expressions
• Lists and related operations
• Conditional Statements
• Related operations of Tuple
• Command Line Arguments
• Strings and related operations
• Python files I/O Functions
• Writing to the Screen
• Creating “Hello World” code
• Set - properties, related operations
• Demonstrating Conditional Statements
• Dictionary - properties, related operations
• Demonstrating Loops
• List - properties, related operations
• Tuple - properties, compared with list and all other related operations
Learning Aim: In this Module of the Python Spark Certification Training using PySpark, the learner shall learn how to create very basic and generic python scripts, and also how to address errors or exceptions in code and furthermore, he would be taught how to filter or extract content through regex.
• Package Installation Ways
• Function Parameters
• Module Search Path
• Global Variables
• Lambda Functions
• Variable Scope and Returning Values
• Object-Oriented Concepts
• The Import Statements
• Modules Used in Python
• Standard Libraries
• Lambda - Syntax, Features, Options, i.e. Compared with the Functions
• Functions - Arguments, Syntax, Keyword Arguments, and Return Values
• Sorting - Sequences, Dictionaries, Limitations of Sorting
• Packages and Module - Import Options, Modules and Systemath
• Errors and Exceptions - Types of Issues, Remediation
Learning Aim: In this module of the PySpark course online, the learner shall be made to comprehend and understand Apache Spark in absolute great depth, and the learner would be learning about different Spark components, he would be creating and also successfully running various spark applications. Finally, you would learn how to perform data ingestion through Sqoop.
• Spark Components & its Architecture
• Introduction to PySpark Shell
• Spark Deployment Modes
• Submitting PySpark Job
• Writing one’s first PySpark Job Through Jupyter Notebook
• Spark Web UI
• Data Ingestion using Sqoop
• Building and Running Spark Application
• Understanding different Spark Properties
• Spark Application Web UI
Learning Objectives: In this module of the PySpark course online, the learner would learn about Spark - RDDs that is accompanied with RDD-related manipulations for implementing the business logics (Actions, Transformations, and Functions performed on the RDD).
• Challenges in Existing Computing Methods
• What is RDD, along with its Operations, Actions, and Transformations.
• Probable Solutions and also How Does RDD Solves the Problem
• Data Loading and Saving Through RDDs
• Other Pair RDDs, Two Pair RDDs
• Key-Value Pair RDDs
• RDD Lineage
• WordCount Program Using RDD Concepts
• RDD Persistence
• RDD Partitioning & How it Helps Achieve
• Passing Functions to Spark
• Loading data in RDDs
• RDD Transformations
• Saving data through RDDs
• RDD Actions and Functions
• WordCount through RDDs
• RDD Partitions
Learning Aim: In this module of the Python Spark Certification Training using PySpark, the learner would learn about SparkSQL used to process structured data with the SQL queries. The learner would learn about data-frames and datasets within Spark SQL along with the different kinds of SQL operations that are performed on the data-frames. The learner would also be taught about Spark and Hive integration.
• Need for Spark SQL
• Spark SQL Architecture
• What is Spark SQL
• SQL Context in Spark SQL
• User-Defined Functions
• Schema RDDs
• Data Frames & Datasets
• JSON and Parquet File Formats
• Interoperating with RDDs
• Spark-Hive Integration
• Loading Data through Different Sources
• Stock Market Analysis
• Spark SQL – Creating data frames
• Spark-Hive Integration
• Loading and transforming data through a different source
Learning Aim: In this module of the PySpark course online, the learner would be taught about the necessity of machine learning, along with the algorithms, techniques, and all of their implementation through Spark MLlib.
• Why Machine Learning
• Where Machine Learning is used
• What is Machine Learning
• Face Detection: USE CASE
• Introduction to MLlib
• Different Types of Machine Learning Techniques
• Various ML algorithms supported by MLlib
• Features of MLlib and MLlib Tools
Learning Aim: In this module of the Python Spark Certification Training using PySpark, the learner would be taught about implementing different algorithms that are supported by MLlib, such as Decision Tree, Linear Regression, Random Forest, and several more.
• Supervised Learning: Logistic Regression Linear Regression, Random Forest and also Decision Tree
• Analysis of the US Election Data via MLlib (K-Means)
• Unsupervised Learning: K-Means Clustering and also How Does It Work with MLlib
• K- Means Clustering
• Logistic Regression
• Linear Regression
• Random Forest
• Decision Tree
Learning Aim: In this module of the PySpark course online, you would be made to understand Kafka and the entire Kafka Architecture. Thereafter, you would also go through the labyrinth details of Kafka Cluster and learn how to configure varied types of Kafka Cluster. You would also be made to view how messages are produced and thereby consumed through Kafka API’s in Java. Furthermore, you would be given an introduction to Apache Flume, and its fundamental architecture and also how it is in conjunction with Apache Kafka for an event processing. You would learn how to ingest streaming data through the flume.
• Requirement for Kafka
• Core Concepts of Kafka
• What is Kafka
• Kafka Architecture
• Understanding the Components of Kafka Cluster
• Where is Kafka Used
• Configuring Kafka Cluster
• Need of Apache Flume
• Kafka Producer and Consumer Java API
• What is Apache Flume
• Flume Sources
• Basic Flume Architecture
• Flume Sinks
• Flume Configuration
• Integrating Apache Flume with Apache Kafka
• Flume Channels
• Configuring Single Node Single Broker Cluster
• Production and also the consumption of messages by way of Kafka Java API
• Configuring Single Node Multi-Broker Cluster
• Flume Commands
• Streaming Twitter Data into HDFS
• Setting up Flume Agent
Learning Aim: In this module of the PySpark course online, the learner shall work in the eclectic domain of Spark streaming that is devised to construct a scalable fault-tolerant application streaming. The learner would learn about DStreams and its several different Transformations that are performed on the streaming data. The learner would get to know regarding the commonly deployed streaming operators such as Stateful Operators and Sliding Window Operators.
• Limitations in Existing Computing Methods
• What is Spark Streaming
• Why Streaming is Necessary
• Features of Spark Streaming
• How Uber Uses Streaming Data
• Spark Streaming Workflow
• Transformations on DStreams
• Streaming Context & DStreams
• Important Windowed Operators
• Stateful Operators
• Slice, Window and Reduce Via Window Operators
• Elucidate Windowed Operators and also Why is it Useful
• WordCounter Program through Spark Streaming
Learning Aim: In this module of the PySpark course online, the learner would learn about the several vast streaming data sources such as the flume and Kafta. Thereafter, towards the end of the module, the learner should be able to create his own Spark Streaming Application.
• Data Sources- Apache Spark Streaming
• Apache Flume and Apache Kafka Data Sources
For Example: Through a Kafka Direct Data Source
• Streaming Data Source Overview
• Different Data Sources of Spark Streaming
• Project 1- Field: Finance
Statement: A leading financial bank endeavors to amplify its financial inclusion for the unbanked population by rendering a safe and positive borrowing experience. In order to ensure that this underserved population has a smooth loan experience, it attempts to use a variety of alternative data that includes telco and other transactional information in order to fathom the repayment abilities of its clients. The bank, therefore, asks the learner to construct a solution so as to make sure that clients who are capable of repayment are not rejected and the loans are shelled out with a maturity, principal, and repayment calendar that would hence empower their clients, thereby making them successful.
Project 2- Field: Media and Entertainment
Statement: Evaluate and deduce the perfect performing movies on the basis of customer feedback and their reviews. Make use of two different API's (Spark DataFrame and Spark RDD) on datasets to gauge the best ranking movies.
Learning Aim: In this module of the PySpark course online, the learner would learn the cardinal concepts of Spark GraphX programming operations and concepts, along with several different GraphX algorithms and their unique implementations in the Python Spark Certification Training using PySpark.
• Introduction to Spark GraphX
• GraphX Basic APIs and Operations
• Information about a Graph
• Spark GraphX Algorithm - PageRank, Triangle Count, Personalized Page Rank, Shortest Paths, Strongly Linked Components, Connected Components, Label Propagation.
• Minimum Spanning Trees
• The Traveling Salesman problem
• Python Spark Course Description
Python Spark Certification Training using PySpark is uniquely curated to render the most sought after and valuable skills and knowledge to don the hat of a successful Big Data and Spark Developer. This Training would unequivocally assist the learner easily and nail the otherwise arduous CCA Spark and Hadoop Developer (CCA175) Examination. The learner would understand the very basics of Hadoop and Big Data. The learner would learn how Spark facilitates in-memory data processing and also runs much faster than Hadoop MapReduce. The learner would also be taught about Spark SQL and RDDs for complex structured processing, along with different APIs furnished by Spark such as Spark MLlib and Spark Streaming. This Python Spark Certification Training using PySpark course online is undoubtedly an integral part of the Big Data Developer’s arduous career path. The Python Spark Certification Training using PySpark course online shall also encompass the very basic albeit pertinent concepts such as data capturing with the aid of messaging system like Kafka, Flume and data loading using Sqoop.
Spark Certification Training has been curated by highly learned, experienced industrial doyens and experts with an envision to make all our learners succeed and Certified Spark Developers. Our PySpark Certification Course offers the following:
• Comprehensive knowledge of several eclectic tools that fall in Spark Ecosystem like Spark MlLib, Sqoop, Kafka, Spark SQL, Spark Streaming, and Flume
• Overview of Hadoop and BigData including HDFS (Hadoop Distributed File System) and also YARN (Yet Another Resource Negotiator)
•The ability of ingesting data in HDFS by way of Flume and Sqoop, and also analysing those large datasets which are stored in the HDFS
• The exposure to several real-life industry-based projects that the learner shall execute through our Cert Ocean’s CloudLab.
• The power of dealing with real-time data feeds via a published and subscribed messaging system like Kafka
• Vigorous involvement of an SME by way of the Spark Training to learn the best industry standards and other practices.
• Projects that are diverse in nature covering telecommunication, banking, social media and other governmental fields.
Spark is one of the most rampantly growing and commonly used tools in the eclectic domain of Big Data and Analytics. This has been ergo adopted by innumerable companies falling into several different categories around the globe and this therefore offers prosperous career opportunities. Also, in order to participate in these different kinds of opportunities, the learner needs a structured training that must work in close conjunction with the Cloudera Hadoop and Spark Developer Certification (CCA175) accompanied with the best practices and current industrial requirements.
Besides having a strong theoretical understanding, it is also very much essential to possess practical, hands-on experience. Therefore, during the Cert Ocean’s PySpark course online, the learner shall be made to work on several used cases that are industry-based, along with projects inculcating big data and spark tools as a part of the unique solution strategy.
Additionally, each and every doubt of the learner shall be addressed by the professionals from different industries, who are currently working on real-life big data and several other data analytics projects.
CerOcean’s PySpark Training has been meticulously designed by experienced industry experts and this greatly aids our learners become a successful Spark developer. Furthermore, during this Python Spark Certification Training using PySpark course, our learners are individually trained by Industry practitioners who hold several years of expert experience in the said field. Also, during the Scala and Apache Spark course, our expert instructors shall thoroughly train our learners, perfecting them to a tee in the following -
• Master the concepts of HDFS
• Learn Spark Streaming
• Understand Hadoop 2.x Architecture
• Understand Spark and its Ecosystem
• Learn data loading techniques using Sqoop
• Implement Spark operations on Spark Shell
• Understand the role of Spark RDD
• Implement Spark applications on YARN (Hadoop)
• Work with RDD in Spark
• Understanding Spark SQL and its labyrinth architecture
• Implement machine learning algorithms such as clustering using Spark MLlib API
• Understand messaging system like Kafka and the components of Kafka
• Utilize Spark Streaming for stream processing of live data
• Integrate real time streaming systems like Flume with Kafka
• Use Kafka to produce and also consume messages from different sources including real time streaming sources such as Twitter
• Solving various real-life industry-based useful cases that would be executed through CertOcean’s CloudLab
Market for Big Data Analytics has mushroomed tremendously all across the world. This extremely strong growth pattern accompanied with constantly augmenting market demand provides a great platform to all the IT Professionals. Below-mentioned are a few Professional IT groups, who are persistently enjoying the immeasurable fruits and perks of venturing into the Big Data domain.
• BI /ETL/DW Professionals
• Developers and Architects
• Data Scientists and Analytics Professionals
• Senior IT Professionals
• Big Data Architects, Developers and Engineers
• Mainframe Professionals
The stats limned below shall render a lucid glimpse of the magnifying popularity along with the growing adoption rate of Big Data tools such as Spark in the current and also in the upcoming years:
• Forbes has estimated that around 56% of Enterprises shall magnify their prior investments in Big Data in the next three years.
• McKinsey had predicted that by 2018 there would be a shortage of around 1.5M data experts, which proved to be true.
• The Spark Developer's average salary is around $113k.
•According to a McKinsey report, the US alone had to deal with a shortage of roughly approximately 190,000 data scientists and also 1.5 million data analysts along with Big Data managers in the year 2018.
It is widely known that nowadays, several big organizations are showing great interest in Big Data and are getting accustomed with Spark as a part of their unique solution strategy. Also, the demand of jobs in Big Data and Spark has been rising tremendously with each passing day. Therefore, it is high time for a learner to pursue their career in the limitless Big Data & Analytics domain with Cert Ocean's uniquely structured PySpark Course Online.
There are no such mandatory prerequisites for CertOcean’s Python Spark Certification Training using PySpark Course online. However, some prior knowledge of SQL and Python Programming shall be greatly helpful, albeit it is not at all necessary.• Python Spark Training Projects
Fret not about the various system requirements as the learner shall be executing all his practicals in CertOcean's Cloud LAB that is a one of its kind, pre-configured environment. This virtual environment already consists of all the required services and tools for PySpark Training at CertOcean's.
Towards the culmination of the PySpark Training, the learner would be assigned with real life case scenarios as certification projects to further hone and polish the learners’ skills and prepare him for the several Spark Developer Roles. Mentioned below are few industry-specific case studies that are included in CertOcean's Apache Spark Developer Training Certification.
Project 1- Field: Financial
Statement: A leading financial bank endeavours to widen its financial inclusion for the unbanked population by furnishing a safe and positive borrowing experience. In order to make sure this underserved population witnesses a smooth and a positive loan experience, the bank makes sure to use of a diverse variety of alternative data that comprises of telco and all other transactional information in order to fathom the repayment abilities of its clients. The bank asks the learner to develop a solution to ensure that clients possessing the ability of repayment must not be rejected and that loans have been given with a maturity, principal and repayment calendar that would empower the clients and make them successful.
Project 2- Field: Transportation Industry
Business requirement/ challenge - With the rise in pollution levels and the fuel prices, several Bicycle Sharing Programs have cropped up all around the globe. Bicycle sharing systems are a unique way of renting bicycles wherein the process of getting a membership, renting and thereafter returning a bike is completely automated through a network of joint locations intricately linked throughout the city. By assiduously deploying this unique system, individuals can rent a bike from one location and thereafter return it at some different place as and when required.
Considerations: The learner shall construct a demand forecasting of bicycle sharing service that clubs historical usage patterns along with weather data to predict and forecast the Bicycle rental demand in real-time. In order to develop this system, the learner must primarily explore the dataset and also construct a model. Once done, the learner needs to persist the model and then run a Spark job on each separate request to load the model and make predictions on all of the Spark Streaming requests.
36 Hours of Online Live Classes. Weekend Class : 12 sessions of 3 hours each. Weekday Class: 18 sessions of 2 hours each.
Real-life Case Studies
Live project based on any of the selected use cases, involving implementation of the various PySpark concepts.
You get lifetime access to LMS where presentations, quizzes, installation guide & class recordings are there.
24 x 7 Expert Support
We have lifetime 24x7 online support team to resolve all your technical queries, through ticket based tracking system.
Sucessfully complete your final course project and Edureka will certify you as a Apache Spark and Scala Developer Using Python.
We have a large community forum for all our learners that further helps learning by virtue of peer interaction and knowledge sharing.
Frequently Asked Questions (FAQs):
A learner won't ever miss a lecture at CertOcean, as he has the liberty to choose either one of the two options below -
• View the recorded session of the class available in LMS.
• Attend any/ all of the missed session, albeit in any other live batch.
A learner shall have round-the-clock, 24/7 access for getting in touch with the Support Team, that would be available at all times, and would cater to all the innumerable student queries, during and after the Python Spark Certification Training using PySpark course online.
To assist our learners in this one of its kind endeavors, we have added a unique and highly useful resume builder tool in all the LMS. Hence, our learners shall be able to create their very own, and an extremely eye-catching resume solely in 3 basic steps. The learner would have an unlimited access to using the several templates across different designations and roles. All that the learner needs to do is to log in to his own LMS and click on "create your resume" option.
Absolutely yes, the entire Pyspark certification course material shall be accessible for a lifetime to a learner, post-enrollment into the Pyspark certification course.
We allow very few, a limited number of participants in our live session in order to maintain our Quality Standards. Hence, unfortunately, participation in a live class without enrolment shall not be possible. However, the learner may go through our sample class recording as this would give a clear insight about how are our classes conducted, and also demonstrate the teaching pedagogy of our highly experienced instructors and the level of student interaction in our unparalleled classes.
All of our instructors at CertOcean are experienced practitioners from the Industry, holding a minimum of 10-12 years relevant experience in IT. Our instructors are subject matter experts and are trained by Cert Ocean for rendering an unparalleled, one of its kind and the most sublime learning experience.
Apache Spark is a one of its kind, unique open-source in-memory, real time cluster processing framework. PySpark is used in streaming analytics systems like the recommendation system and the bank fraud detection system etc. Whereas Python is a high-level, general-purpose programming language. It has a heterogeneous range of libraries that assist several types of different applications. PySpark is a wonderful blend of Python and Spark. It caters to the Python API for Spark that permits the learner to gauge the very fundamental simplicity of Python along with the power of Apache Spark to handle Big Data.
RDD alludes to Resilient Distributed Dataset that is the building block of the Apache Spark. RDD is fundamental data structure of Apache Spark that is also an unchangeable and a distributed collection of objects. All the datasets in RDD are further subdivided into smaller logical partitions that can be later computed via different cluster nodes.
No, Pyspark is not a language. Python Spark Certification Training using PySpark is rather a Python API for Apache Spark through which Python developers can augment the power of Apache Spark and manifest in-memory processing applications. Furthermore, Python Spark Certification Training using PySpark is developed to assist the rapidly growing and uncountable Python community.