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Pyspark Certification Course

512 Ratings

This PySpark course is Designed by industry experts to help you master PySpark skills and become a certified developer of the technology through real-time projects and case studies. Get advantage of the PySpark training from domain experts who have years of experience in the field and clear CCA175 certification exam. Enroll Now!

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Key Highlights

24 Hrs Instructor Led Training
22 Hrs Self-paced Videos
60 Hrs Project & Exercises
Certification
Job Assistance
Flexible Schedule
Lifetime Free Upgrade
Mentor Support
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PySpark Course Overview

What will you learn in this PySpark Course?

When you enroll in our PySpark certification course and complete the certification program, you will:

  • Become familiar with Apache Spark, its applicability and Spark 2.0 architecture
  • Gain hands-on expertise with the various tools in the Spark ecosystem, including Spark MLlib, Spark SQL, Kafka, Flume and Spark Streaming
  • Understand the architecture of RDD, lazy evaluation, etc.
  • Learn how to change the architecture of the DataFrame and how to interact with it using Spark SQL
  • Build various APIs that work with Spark DataFrame
  • Pick up the skills to aggregate, filter, sort and transform data using DataFrame

Big Data analytics is experiencing constant growth, thus, providing an excellent opportunity for all IT kinds of IT/ITES professionals. Thus, learning the technology is an outstanding career transition. Further, professional hailing from the following domains can enroll in our best PySpark course online:

  • Software developers and architects
  • ETL and DW professionals
  • BI experts
  • Senior IT expert
  • Mainframe developers
  • Data Science engineers
  • Big data engineers, developers, and architects, etc.

We do not enforce any prerequisite for enrolling in our PySpark training online. However, basic programming skills can help you speed up your learning. However, you can still join our PySpark Certification Program without any extensive programming experience. Our online real-time teaching is conducted by industry experts, and under their guidance, you can easily pick up the basics of any topic/domain.

  • In the US, Data Spark Developer has an average annual salary of $150,000 – Neuvoo
  • The average salary range for “Apache Spark Developers” is from US$92,176 a year for the developer to $126,114 a year for back-end developers. – Indeed
  • Big data market revenue is expected to grow from $42 billion (2018) to $103 billion in 2027! – Forbes
  • 79% of company executives say that companies that do not embrace Big Data are losing market control and may become non-existent – Accenture

Almost all the companies that rely on Big Data, use Spark as part of their solution strategy. Therefore, the job requirements in either Big Data or PySpark are not going to reduce in the upcoming years. So, “now,” is the perfect time to upskill your PySpark learning and enroll yourself in a recognized PySpark training course.

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PySpark Course Fees

Self Paced Training

  • 22 Hrs e-learning videos
  • Flexible Schedule
  • Lifetime Free Upgrade

$264

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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PySpark Course Curriculum

Live Course Self Paced

Introduction to the Basics of Python

Preview
  • Explaining Python and Highlighting Its Importance
  • Setting up Python Environment and Discussing Flow Control
  • Running Python Scripts and Exploring Python Editors and IDEs
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Sequence and File Operations

Preview
  • Defining Reserve Keywords and Command Line Arguments
  • Describing Flow Control and Sequencing
  • Indexing and Slicing
  • Learning the xrange() Function
  • Working Around Dictionaries and Sets
  • Working with Files
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  • Explaining Functions and Various Forms of Function Arguments
  • Learning Variable Scope, Function Parameters, and Lambda Functions
  • Sorting Using Python
  • Exception Handling
  • Package Installation
  • Regular Expressions
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  • Using Class, Objects, and Attributes
  • Developing Applications Based on OOP
  • Learning About Classes, Objects and How They Function Together
  • Explaining OOPs Concepts Including Inheritance, Encapsulation, and Polymorphism, Among Others
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  • Spark Components & its Architecture
  • Spark Deployment Modes
  • Spark Web UI
  • Introduction to PySpark Shell
  • Submitting PySpark Job
  • Writing your first PySpark Job Using Jupyter Notebook
  • What is Spark RDDs?
  • Stopgaps in existing computing methodologies
  • How RDD solve the problem?
  • What are the ways to create RDD in PySpark?
  • RDD persistence and caching
  • General operations: Transformation, Actions, and Functions
  • Concept of Key-Value pair in RDDs
  • Other pair, 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:

  • Building and Running Spark Application
  • Spark Application Web UI
  • Loading data in RDDs
  • Saving data through RDDs
  • RDD Transformations
  • RDD Actions and Functions
  • RDD Partitions
  • WordCount program using RDD’s in Python
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  • Need for Spark SQL
  • What is Spark SQL
  • Spark SQL Architecture
  • SQL Context in Spark SQL
  • User-Defined Functions
  • Data Frames
  • Interoperating with RDDs
  • Loading Data through Different Sources
  • Performance Tuning
  • Spark-Hive Integration

Hands-On:

  • Spark SQL – Creating data frames
  • Loading and transforming data through different sources
  • Spark-Hive Integration
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  • Why Kafka
  • What is Kafka?
  • Kafka Workflow
  • Kafka Architecture
  • Kafka Cluster Configuring
  • Kafka Monitoring tools
  • Basic operations
  • What is Apache Flume?
  • Integrating Apache Flume and Apache Kafka

Hands-On:

  • Single Broker Kafka Cluster
  • Multi-Broker Kafka Cluster
  • Topic Operations
  • Integrating Apache Flume and Apache Kafka
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  • Introduction to Spark Streaming
  • Features of Spark Streaming
  • Spark Streaming Workflow
  • StreamingContext Initializing
  • Discretized Streams (DStreams)
  • Input DStreams, Receivers
  • Transformations on DStreams
  • DStreams Output Operations
  • Describe Windowed Operators and Why it is Useful
  • Stateful Operators
  • Vital Windowed Operators
  • Twitter Sentiment Analysis
  • Streaming using Netcat server
  • WordCount program using Kafka-Spark Streaming

Hands-On:

  • Twitter Sentiment Analysis
  • Streaming using Netcat server
  • WordCount program using Kafka-Spark Streaming
  • Spark-flume Integration
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  • Introduction to Machine Learning- What, Why and Where?
  • Use Case
  • Types of Machine Learning Techniques
  • Why use Machine Learning for Spark?
  • Applications of Machine Learning (general)
  • Applications of Machine Learning with Spark
  • Introduction to MLlib
  • Features of MLlib and MLlib Tools
  • Various ML algorithms supported by MLlib
  • Supervised Learning Algorithms
  • Unsupervised Learning Algorithms
  • ML workflow utilities

Hands-On:

  • K- Means Clustering
  • Linear Regression
  • Logistic Regression
  • Decision Tree
  • Random Forest
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Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!

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Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 20+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions and that will help you stay on track with your up-skilling objective.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & LinkedIn Profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through several mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learners’ educational background, experience, and future career aspirations.

Assured Interviews

After 80% of the course completion

Assured Interviews upon submission of projects and assignments. Get interviewed by our 500+ hiring partners.

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

PySpark Certification

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Intellipaat’s PySpark course is designed to help you gain insight into the various PySpark concepts and pass the CCA Spark and Hadoop Developer Exam (CCA175). The entire program is created by industry experts to help professionals gain top positions in leading organizations. Our certification program on PySpark is planned and conducted according to the requirements of the certification exam.

In addition, industry-specific projects and hands-on experience with a variety of Spark tools can help you accelerate your learning. After completing the program, you will be asked to complete a quiz, which is based on the questions asked in the PySpark certification exam. Besides, we also award each candidate with Intellipaat PySpark Course Completion Certificate after he/she completes entire program along with the projects and scores the passing marks in the quiz.

Our course completion certification in PySpark is recognized across the industry and many of our alumni work at leading MNCs, including Sony, IBM, Cisco, TCS, Infosys, Amazon, Standard Chartered, and more.

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Frequently Asked Questions on PySpark

What is Intellipaat’s PySpark online classroom training?

The PySpark online classroom sessions at Intellipaat involves the simultaneous participation of learners and teachers in the online environment. As a participant, you can log in and take PySpark classes from anywhere, without having to be present in person. Moreover, all sessions are recorded and made accessible via the LMS within 24 hours of the learning session. This PySpark online training combines live instructor-led training, self-paced classes, online videos, 24/7 live support, and multiple assignments. Further, we provide lifetime access to our learning videos and other contents along with free upgrades to the latest version of the course curriculum.

After completing this program, your PySpark skills will be equivalent to a professional with 6-month experience in the same industry.

3 technical 1:1 sessions per month will be allowed.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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