NobleProg delivers high-quality Hadoop training courses in Berlin, the dynamic heart of Germany's tech and innovation sector. Participants benefit from expert-led instruction tailored to the professional needs of the capital's diverse industry landscape. Join our Berlin-based programs to enhance your skills with hands-on learning experiences in a world-class urban environment.
Whether delivered online or in person, our instructor-led live Apache Hadoop courses offer an immersive learning experience. Through interactive, hands-on exercises, participants explore the core components of the Hadoop ecosystem and discover how these technologies address large-scale data challenges.
Hadoop instruction is available as either "online live training" or "onsite live training." Online live training, also known as remote live training, is conducted via an interactive remote desktop environment. Onsite live training can be hosted locally at customer premises in Berlin or within NobleProg’s corporate training facilities in Berlin.
Our training facilities are located at Brückenstr. 4 in Berlin. Located on the fourth floor of a well-kept office building, our premises offer enough space for successful training courses in the heart of Berlin, within walking distance of the Jannowitzbrücke station.
Directions
The NobleProg training facilities are located in the heart of Berlin's Mitte district, just one underground station from Alexanderplatz, one of the centres of this vibrant city. By public transport you can reach us either by underground line U8 to Jannowitzbrücke station, followed by about 100 meters on foot.
Parking
Cars can be parked in the area along Brückenstr. and the nearby side streets, even if you may have to search for a moment. There is no charge for parking.
Local Amenities
Around the Rosenthaler Platz there are numerous small restaurants and shops where you can eat well and cheaply. There are also some hotels close by if you need accommodation for the training.
Our training facilities are located at Dianastrasse 46 in Potsdam-Babelsberg.
Our spacious training rooms are located directly opposite the Filmstudios Babelsberg and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the Medienstadt Babelsberg railway station,
and the A115 motorway is also easily accessible.
Parking
Parking is available in the surrounding streets around our training rooms.
Local Services
Potsdam offers numerous hotels and restaurants and is easily accessible thanks to its well-developed public transport system.
This live, instructor-led training session, delivered either online or onsite, is tailored for developers looking to harness the power of Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets.
By the conclusion of this training, participants will be able to:
Establish the necessary environment to begin processing big data using Spark, Hadoop, and Python.
Comprehend the features, core components, and architecture of Spark and Hadoop.
Apply knowledge on integrating Spark, Hadoop, and Python for efficient big data processing.
Explore the tools within the Spark ecosystem, such as Spark MlLib, Spark Streaming, Kafka, Sqoop, and Flume.
Construct collaborative filtering recommendation systems similar to those found on Netflix, YouTube, Amazon, Spotify, and Google.
Implement Apache Mahout to scale machine learning algorithms effectively.
This live, instructor-led training in Berlin is crafted for intermediate administrators looking to deploy and manage Apache NiFi in production settings. Learners will acquire the skills to configure clusters, design dataflows, and enhance performance through practical labs and scenario-based exercises.
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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.
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