PySpark for Data Engineers: From Beginner to Expert

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Data Processing with PySpark Course Overview

Data Processing with PySpark is a course or training program that focuses on teaching individuals how to process large data sets using Apache Spark and PySpark, a Python library for Apache Spark. The course covers the basics of Spark and its architecture, as well as how to perform common data processing tasks such as data filtering, aggregation, and transformation using PySpark. The course also covers advanced topics such as working with Spark data frames, machine learning with Spark, and deployment and scaling of Spark applications. The target audience for this course is data engineers, data scientists, and software developers who want to work with large data sets in a distributed computing environment. The prerequisites for this course include a basic understanding of Python programming, SQL, and familiarity with data processing concepts.

Target Audience:

  • Data Engineers: those who work with large data sets and want to learn how to efficiently process and store data using Apache Spark and PySpark.
  • Data Scientists: individuals who perform data analysis and modeling and want to learn how to use Spark and PySpark to scale their data processing capabilities.
  • Software Developers: professionals who want to learn how to build and deploy Spark applications for large-scale data processing.
  • Big Data Enthusiasts: those who are interested in learning about Big Data technologies and want to work with Apache Spark and PySpark.
  • IT Professionals: individuals working in IT who want to gain knowledge and skills in distributed data processing using Spark and PySpark.

Learning Objectives:

  • Understanding Apache Spark and its architecture: gain knowledge about Spark and its components, including the Spark driver, executors, and RDDs.
  • Working with PySpark: learn how to use PySpark for data processing, including reading and writing data, performing transformations, and aggregations.
  • Manipulating Spark DataFrames: learn how to work with Spark data frames and perform operations such as filtering, grouping, and joining data.
  • Implementing Machine Learning with Spark: learn how to perform machine learning tasks using Spark MLlib, including regression, classification, and clustering.
  • Deploying and Scaling Spark Applications: learn how to deploy Spark applications in a cluster environment, including tuning and optimizing Spark applications for performance.
  • Integrating Spark with other Big Data Technologies: learn how to integrate Spark with other Big Data technologies, such as Hadoop, Hive, and Cassandra.
  • Best Practices for Data Processing with PySpark: learn best practices for data processing with Spark, including data pre-processing, partitioning, and error handling.
 
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The 1-on-1 Advantage

Get 1on-1 session with our expert trainers at a date & time of your convenience.
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Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
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4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.
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Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.
Live Online Training (Duration : 32 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

1600 + If you accept merging of other students. Per Participant & excluding VAT/GST
4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
1400 Per Participant & excluding VAT/GST
Online
05 - 08 Jun
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Online
03 - 06 Jul
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Course Prerequisites
  • Basic knowledge of Python programming: participants should have a basic understanding of Python syntax and be able to write simple programs.
  • Familiarity with SQL: participants should have basic knowledge of SQL and be able to write simple SQL queries.
  • Understanding of data processing concepts: participants should have a basic understanding of data processing concepts, including data structures, algorithms, and data manipulations.
  • Familiarity with Big Data technologies: having some prior experience with Big Data technologies such as Hadoop, Hive, and Cassandra could be beneficial.
  • Knowledge of statistics and mathematics: basic knowledge of statistics and linear algebra could be helpful for understanding some of the concepts covered in the course.

FAQ's


Yes, fee excludes local taxes.
Yes, we do.
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).
1-on-1 Public - Select your start date. Other students can be merged. 1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
Yes, you can pay from the course page and flexi page.
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We use the best standards in Internet security. Any data retained is not shared with third parties.
You can request a refund if you do not wish to enroll in the course.
To receive an acknowledgment of your online payment, you should have a valid email address. At the point when you enter your name, Visa, and other data, you have the option of entering your email address. Would it be a good idea for you to decide to enter your email address, confirmation of your payment will be emailed to you.
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We do accept all major credit cards from Visa, Mastercard, American Express, and Discover.
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Yes, we do accept partial payments, you may use one payment method for part of the transaction and another payment method for other parts of the transaction.
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Yes, we do offer corporate training More details
Yes, we do.
Yes, we also offer weekend classes.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes. You can access courseware for most vendors.
Yes, this is our official email address which we use if a recipient is not able to receive emails from our @koenig-solutions.com email address.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
You will receive the digital certificate post training completion via learning enhancement tool after registration.
Yes you can.
Yes, we do. For details go to flexi
You can pay through debit/credit card or bank wire transfer.
Dubai, London, Sydney, Singapore, New York, Delhi, Goa, Bangalore, Chennai and Gurugram.
Yes you can request your customer experience manager for the same.
Yes of course. 100% refund if training not upto your satisfaction.

Prices & Payments

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Travel and Visa

Yes we do after your registration for course.

Food and Beverages

Yes.

Others

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