Online or onsite, instructor-led live Apache Hadoop training courses demonstrate through interactive hands-on practice the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems.
Hadoop 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 Hadoop training can be carried out locally on customer premises in Cardiff or in NobleProg corporate training centers in Cardiff.
NobleProg -- Your Local Training Provider
Cardiff
Radisson Blu Hotel, Meridian Gate - Bute Terrace, Cardiff, united kingdom, CF10 2FL
The Radisson Blu Hotel in Cardiff city centre is the perfect hub for your Welsh adventure
Close to several public transportation options, our hotel in Cardiff puts the city centre at your fingertips. Catch a train or a bus at one of the nearby stations, or take the M4 motorway and drive wherever you want to go in Wales and beyond. For those flying into the city, the Cardiff International Airport is just a 30-minute drive from the hotel. You’ll find parking around the hotel at the John Lewis, St David’s II and NCP Pellet Street car parks, plus some parking at the hotel. Enjoy shopping and dining within walking distance of the hotel, and explore the colourful history of this thriving capital city.
The hotel is located on Bute Terrace providing easy access to the M4 at junction 32 only 6 km away.
The central train and bus station is located within a five-minute walk from the hotel.
Cardiff International Airport is located 24 km from the hotel and can be reached by bus, train or taxi.
This instructor-led, live training in Cardiff (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.
Apache NiFi is an open-source, flow-based data integration and event-processing platform. It enables automated, real-time data routing, transformation, and system mediation between disparate systems, with a web-based UI and fine-grained control.
This instructor-led, live training (onsite or remote) is aimed at intermediate-level administrators and engineers who wish to deploy, manage, secure, and optimise NiFi dataflows in production environments.
By the end of this training, participants will be able to:
Install, configure, and maintain Apache NiFi clusters.
Design and manage dataflows from varied sources and sinks.
Implement flow automation, routing, and transformation logic.
Optimize performance, monitor operations, and troubleshoot issues.
Format of the Course
Interactive lecture with real-world architecture discussion.
Hands-on labs: building, deploying, and managing flows.
Scenario-based exercises in a live-lab environment.
Course Customisation Options
To request a customised training for this course, please contact us to arrange.
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Testimonials (2)
Hands on exercises. Class should have been 5 days, but the 3 days helped to clear up a lot of questions that I had from working with NiFi already
James - BHG Financial
Course - Apache NiFi for Administrators
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
Provisional Upcoming Courses (Contact Us For More Information)
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