Apache Spark is a fast and open-source engine for big data processing.
NobleProg onsite 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 in various formats, including onsite live training and live instructor-led training using an interactive, remote desktop setup. Local Apache Spark training can be carried out live on customer premises or in NobleProg local training centers.
We know know a lot more about the whole environment
John Kidd - Cardano Risk Management
Course Name: Spark for Developers
Ernesto did a great job explaining the high level concepts of using Spark and it's various modules.
Michael Nemerouf -
Course Name: Spark for Developers
I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.
Course Name: Spark for Developers
I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.
Course Name: Spark for Developers
The trainer made the class interesting and entertaining which helps quite a bit with all day trainings
Ryan Speelman -
Course Name: Spark for Developers
Richard is very calm and methodical, with an analytical insight - exactly the qualities needed to present this sort of course
Kieran Mac Kenna - BAE Systems Applied Intelligence
Course Name: Spark for Developers
Me gusto la metodologia esperada por Jorge
Experian Colombia S.A
Course Name: Spark para Desarrolladores
If the teacher can speak slowly, it is perfect.
Nicole Song Fmr
Course Name: Spark for Developers
Translated by
如果老师能讲话慢一点，就perfect了。
Nicole Song - Fmr
all parts of this session
Eric Han Fmr
Course Name: Spark for Developers
Translated by
all parts of this session
Eric Han - Fmr
case analysis
Zhang Guodong Fmr
Course Name: Spark for Developers
Translated by
案例分析
张 国栋 - Fmr
| Code | Name | Venue | Duration | Course Date | PHP | Course Price [Remote / Classroom] |
|---|---|---|---|---|---|---|
| hdp | Hortonworks Data Platform (HDP) for administrators | Birmingham | 21 hours | Tue, 2018-05-15 09:30 | £3300 / £4275 | |
| graphcomputing | Introduction to Graph Computing | Birmingham | 28 hours | Tue, 2018-05-22 09:30 | £4400 / £5700 | |
| magellan | Magellan: Geospatial Analytics on Spark | Birmingham | 14 hours | Tue, 2018-05-22 09:30 | £2600 / £3250 | |
| alluxio | Alluxio: Unifying disparate storage systems | Birmingham | 7 hours | Thu, 2018-05-24 09:30 | £1100 / £1425 | |
| sparkpython | Python and Spark for Big Data (PySpark) | Birmingham | 21 hours | Wed, 2018-05-30 09:30 | £3900 / £4875 | |
| 68780 | Apache Spark | Birmingham | 14 hours | Thu, 2018-05-31 09:30 | £2200 / £2850 | |
| sparksql | Apache Spark SQL | Birmingham | 7 hours | Thu, 2018-06-14 09:30 | £1100 / £1425 | |
| sparkdev | Spark for Developers | Birmingham | 21 hours | Tue, 2018-06-19 09:30 | £3300 / £4275 | |
| introtostreamprocessing | A Practical Introduction to Stream Processing | Birmingham | 21 hours | Mon, 2018-07-02 09:30 | £3300 / £4275 | |
| hdp | Hortonworks Data Platform (HDP) for administrators | Birmingham | 21 hours | Mon, 2018-07-09 09:30 | £3300 / £4275 | |
| magellan | Magellan: Geospatial Analytics on Spark | Birmingham | 14 hours | Wed, 2018-07-11 09:30 | £2600 / £3250 | |
| alluxio | Alluxio: Unifying disparate storage systems | Birmingham | 7 hours | Thu, 2018-07-12 09:30 | £1100 / £1425 | |
| graphcomputing | Introduction to Graph Computing | Birmingham | 28 hours | Mon, 2018-07-16 09:30 | £4400 / £5700 | |
| 68780 | Apache Spark | Birmingham | 14 hours | Mon, 2018-07-23 09:30 | £2200 / £2850 | |
| sparkdev | Spark for Developers | Birmingham | 21 hours | Tue, 2018-08-14 09:30 | £3300 / £4275 | |
| sparkpython | Python and Spark for Big Data (PySpark) | Birmingham | 21 hours | Wed, 2018-08-22 09:30 | £3900 / £4875 | |
| introtostreamprocessing | A Practical Introduction to Stream Processing | Birmingham | 21 hours | Wed, 2018-08-29 09:30 | £3300 / £4275 | |
| magellan | Magellan: Geospatial Analytics on Spark | Birmingham | 14 hours | Thu, 2018-08-30 09:30 | £2600 / £3250 | |
| sparksql | Apache Spark SQL | Birmingham | 7 hours | Thu, 2018-08-30 09:30 | £1100 / £1425 | |
| hdp | Hortonworks Data Platform (HDP) for administrators | Birmingham | 21 hours | Wed, 2018-09-05 09:30 | £3300 / £4275 | |
| graphcomputing | Introduction to Graph Computing | Birmingham | 28 hours | Tue, 2018-09-11 09:30 | £4400 / £5700 | |
| alluxio | Alluxio: Unifying disparate storage systems | Birmingham | 7 hours | Wed, 2018-09-12 09:30 | £1100 / £1425 | |
| 68780 | Apache Spark | Birmingham | 14 hours | Wed, 2018-09-19 09:30 | £2200 / £2850 | |
| sparkdev | Spark for Developers | Birmingham | 21 hours | Mon, 2018-10-15 09:30 | £3300 / £4275 | |
| sparkpython | Python and Spark for Big Data (PySpark) | Birmingham | 21 hours | Mon, 2018-10-15 09:30 | £3900 / £4875 | |
| sparksql | Apache Spark SQL | Birmingham | 7 hours | Fri, 2018-10-19 09:30 | £1100 / £1425 | |
| magellan | Magellan: Geospatial Analytics on Spark | Birmingham | 14 hours | Mon, 2018-10-22 09:30 | £2600 / £3250 | |
| introtostreamprocessing | A Practical Introduction to Stream Processing | Birmingham | 21 hours | Tue, 2018-10-23 09:30 | £3300 / £4275 | |
| hdp | Hortonworks Data Platform (HDP) for administrators | Birmingham | 21 hours | Tue, 2018-10-30 09:30 | £3300 / £4275 | |
| alluxio | Alluxio: Unifying disparate storage systems | Birmingham | 7 hours | Mon, 2018-11-05 09:30 | £1100 / £1425 | |
| graphcomputing | Introduction to Graph Computing | Birmingham | 28 hours | Mon, 2018-11-05 09:30 | £4400 / £5700 | |
| 68780 | Apache Spark | Birmingham | 14 hours | Thu, 2018-11-08 09:30 | £2200 / £2850 |
| Code | Name | Duration | Outline |
|---|---|---|---|
| 68780 | Apache Spark | 14 hours | |
| sparkdev | Spark for Developers | 21 hours |
OBJECTIVE:This course will introduce Apache Spark. The students will learn how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis. The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX. AUDIENCE :Developers / Data Analysts |
| hdp | Hortonworks Data Platform (HDP) for administrators | 21 hours |
Hortonworks Data Platform is an open-source Apache Hadoop support platform that provides a stable foundation for developing big data solutions on the Apache Hadoop ecosystem. This instructor-led live training introduces Hortonworks and walks participants through the deployment of Spark + Hadoop solution. By the end of this training, participants will be able to:
Audience
Format of the course
|
| magellan | Magellan: Geospatial Analytics on Spark | 14 hours |
Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics. This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark. By the end of this training, participants will be able to:
Audience
Format of the course
|
| alluxio | Alluxio: Unifying disparate storage systems | 7 hours |
Alexio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba. In this instructor-led, live training, participants will learn how to use Alexio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio. By the end of this training, participants will be able to:
Audience
Format of the course
|
| graphcomputing | Introduction to Graph Computing | 28 hours |
A large number of real world problems can be described in terms of graphs. For example, the Web graph, the social network graph, the train network graph and the language graph. These graphs tend to be extremely large; processing them requires a specialized set of tools and processes -- these tools and processes can be referred to as Graph Computing (also known as Graph Analytics). In this instructor-led, live training, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a graph computing approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments. By the end of this training, participants will be able to:
Audience
Format of the course
|
| sparkpython | Python and Spark for Big Data (PySpark) | 21 hours |
Python is a high-level programming language famous for its clear syntax and code readibility. Spark is a data processing engine used in querying, analyzing, and transforming big data. PySpark allows users to interface Spark with Python. In this instructor-led, live training, 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:
Audience
Format of the course
|
| sparksql | Apache Spark SQL | 7 hours |
Spark SQL is Apache Spark's module for working with structured and unstructured data. Spark SQL provides information about the structure of the data as well as the computation being performed. This information can be used to perform optimizations. Two common uses for Spark SQL are: In this instructor-led, live training (onsite or remote), participants will learn how to analyze various types of data sets using Spark SQL. By the end of this training, participants will be able to:
Audience
Format of the Course
Notes
|
| introtostreamprocessing | A Practical Introduction to Stream Processing | 21 hours |
Stream Processing refers to the real-time processing of "data in motion", that is, performing computations on data as it is being received. Such data is read as continuous streams from data sources such as sensor events, website user activity, financial trades, credit card swipes, click streams, etc. Stream Processing frameworks are able to read large volumes of incoming data and provide valuable insights almost instantaneously. In this instructor-led, live training (onsite or remote), participants will learn how to setup and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices. By the end of this training, participants will be able to:
Audience
Format of the Course
Notes
|