Online or onsite, instructor-led live Apache Spark training courses demonstrate through hands-on practice how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis.
Apache Spark training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Apache Spark training can be carried out locally on customer premises in Newcastle or in NobleProg corporate training centers in Newcastle.
NobleProg -- Your Local Training Provider
Newcastle
116 Quayside, Newcastle upon Tyne, united kingdom, NE1 3DY
The Newcastle Quayside Centre is in a prestigious riverside location close to the River Tyne occupying three floors of a five-storey building with a glass front and modern interior. The views of the famous Tyne Bridge and recently built Millennium Bridge are stunning. The recently restored Baltic Centre for Contemporary Art is directly opposite, next to the Sage Gateshead performing arts and conference centre. The vibrant and energetic city of Newcastle is a modern, attractive and compact location with a strong identity where businesses prosper and people enjoy a quality of life that is second to none. This area is among the most successful in the UK for attracting investment from abroad and is already the preferred location of many Far Eastern and US companies entering the European market. Over 130 investors from 15 countries have chosen to locate in and around the city, joining a business community of over 17,000 companies.
This instructor-led, live training in Newcastle (online or onsite) is aimed at intermediate-level data scientists and engineers who wish to use Google Colab and Apache Spark for big data processing and analytics.
By the end of this training, participants will be able to:
Set up a big data environment using Google Colab and Spark.
Process and analyze large datasets efficiently with Apache Spark.
Visualize big data in a collaborative environment.
Stratio is a data-centric platform that integrates big data, AI, and governance into a single solution. Its Rocket and Intelligence modules enable rapid data exploration, transformation, and advanced analytics in enterprise environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level data professionals who wish to use the Rocket and Intelligence modules in Stratio effectively with PySpark, focusing on looping structures, user-defined functions, and advanced data logic.
By the end of this training, participants will be able to:
Navigate and work within the Stratio platform using Rocket and Intelligence modules.
Apply PySpark in the context of data ingestion, transformation, and analysis.
Use loops and conditional logic to control data workflows and feature engineering tasks.
Create and manage user-defined functions (UDFs) for reusable data operations in PySpark.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customisation Options
To request a customised training for this course, please contact us to arrange.
This instructor-led, live training in Newcastle (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets.
By the end of this training, participants will be able to:
Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
Understand the features, core components, and architecture of Spark and Hadoop.
Learn how to integrate Spark, Hadoop, and Python for big data processing.
Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
Use Apache Mahout to scale machine learning algorithms.
This instructor-led, live training in Newcastle (online or onsite) is aimed at beginner-level to intermediate-level system administrators who wish to deploy, maintain, and optimise Spark clusters.
By the end of this training, participants will be able to:
Install and configure Apache Spark in various environments.
Manage cluster resources and monitor Spark applications.
Optimize the performance of Spark clusters.
Implement security measures and ensure high availability.
In this instructor-led, live training in Newcastle, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.
By the end of this training, participants will be able to:
Learn how to use Spark with Python to analyze Big Data.
Work on exercises that mimic real world cases.
Use different tools and techniques for big data analysis using PySpark.
This training provides a practical introduction to building scalable data processing and Machine Learning workflows using PySpark. Participants learn how Apache Spark operates within modern Big Data ecosystems and how to efficiently process large datasets using distributed computing principles.
This instructor-led, live training in Newcastle (online or onsite) is aimed at engineers who wish to set up and deploy Apache Spark system for processing very large amounts of data.
By the end of this training, participants will be able to:
Install and configure Apache Spark.
Quickly process and analyze very large data sets.
Understand the difference between Apache Spark and Hadoop MapReduce and when to use which.
Integrate Apache Spark with other machine learning tools.
Apache Spark's learning curve is slowly increasing at the begining, it needs a lot of effort to get the first return. This course aims to jump through the first tough part. After taking this course the participants will understand the basics of Apache Spark , they will clearly differentiate RDD from DataFrame, they will learn Python and Scala API, they will understand executors and tasks, etc. Also following the best practices, this course strongly focuses on cloud deployment, Databricks and AWS. The students will also understand the differences between AWS EMR and AWS Glue, one of the lastest Spark service of AWS.
AUDIENCE:
Data Engineer, DevOps, Data Scientist
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Testimonials (3)
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.
Raul Mihail Rat - Accenture Industrial SS
Course - Python, Spark, and Hadoop for Big Data
Having hands on session / assignments
Poornima Chenthamarakshan - Intelligent Medical Objects
Course - Apache Spark in the Cloud
Provisional Upcoming Courses (Contact Us For More Information)
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