NY, Long Island - Bohemia

80 Orville Drive Suite 100, Bohemia, united states, 11716

The venue is located just across the road from the Puritan's Pride Vitamin Factory Outlet and the Leidel Corporation building, just up the road from FedEx.

PA, Pittsburgh - Penn Center East Monroeville

201 Penn Center Boulevard Suite 400, Pittsburgh, United states, 15235

The venue is located in the neighborhood of the Penn Center, on the opposite side of the street to the Rey Azteca and Yamato restaurants and in the same building as Pearce Orthodontics.

NY, Brooklyn - One Pierrepont Plaza

300 Cadman Plaza West, New York, united states, 11201

One Pierrepont Plaza is accessible via 12 nearby subway and bus lines. The building is conveniently located near the Brooklyn Bridge, the Manhattan Bridge and the Brooklyn-Queens Expressway. Long Island Rail Road within walking distance and 5 minutes to downtown Manhattan.

NY, Long Island - New Hyde Park

1979 Marcus Ave Suite 210, Long Island, united states, 11042

The Center is located within three miles from The Long Island Expressway, Northern State Parkway and MTA bus. There is fast access to amenities close by and an easy commute to the city with only 15 minutes drive to LaGuardia and Kennedy Airports.

CT, Stamford - Downtown

One Stamford Plaza, Stamford, united states, 06901

The venue is located just opposite of the Stamford Mariott Hotel & Spa and in the vicinity of the Stamford Town Center, H&M and Barnes&Noble.

CT, Hartford - Downtown

CT, Hardford - Downtown, 100 Pearl Street 14th floor, Hartford, united states, 06103

The venue is located right at the heart of the city's business district in the Greater Hartford Welcome Center, just opposite of the Pearl St and Lewis St bus station. This impressive two-tower office building features a three-story granite and glass lobby its own gym and a secure underground parking.

CT, East Berlin - East Berlin

East Berlin, 1224 Mill St. Building B - Suite 224, East Berlin, united states, 06023

The venue is located just off of Mill St in the vicinity of Haven, Inc.

PA, Philadelphia - International Plaza Dr Suite

1 International Plaza Dr Suite 550, Philadelphia, united states, 19153

The Center lies in the heart of Philadelphia with excellent highway access to I-95. It is in a short distance to City Center train depot, SEPTA bus and offers shuttle service to nearby Philadelphia International Airport.

NY, Queens - Forest Hills Tower

Queens Blvd Suite 400, New York, united states, 11375

This venue is situated on the corner with Grand Central Parkway / Jackie Robinson Parkway giving you quick subway access. It is conveniently located in less than 30 minutes from Long Island and only 15 minutes away from JFK and LaGuardia Airports.

NY, Staten Island - 1120 South Avenue

1120 South Ave, Staten Island, united states, 10314

This location is located right off the Staten Island Expressway, 6 miles from Historic Richmond Town and 7 miles from the Staten Island Ferry to Lower Manhattan.

Subcategories (3)

GraphX

GraphX
Apache Spark MLlib

Apache Spark MLlib
PySpark

PySpark

Explore Our Courses

Big Data Analytics with Google Colab and Apache Spark

 14 Hours
This instructor-led, live training in New York (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.
  • Integrate Apache Spark with cloud-based tools.
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Python, Spark, and Hadoop for Big Data

 21 Hours
This instructor-led, live training in New York (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.
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Administration of Apache Spark

 35 Hours
This instructor-led, live training in New York (online or onsite) is aimed at beginner-level to intermediate-level system administrators who wish to deploy, maintain, and optimize 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.
  • Debug and troubleshoot common Spark issues.
Read more...

Python and Spark for Big Data (PySpark)

 21 Hours
In this instructor-led, live training in New York, 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.
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Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

 21 Hours
This course is intended for developers and data scientists who want to understand and implement artificial intelligence in their applications. Special focus is placed on data analytics, distributed AI, and natural language processing.
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Big Data Analytics in Health

 21 Hours
Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights. The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment. In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises. By the end of this training, participants will be able to:
  • Install and configure big data analytics tools such as Hadoop MapReduce and Spark
  • Understand the characteristics of medical data
  • Apply big data techniques to deal with medical data
  • Study big data systems and algorithms in the context of health applications
Audience
  • Developers
  • Data Scientists
Format of the Course
  • Part lecture, part discussion, exercises and heavy hands-on practice.
Note
  • To request a customized training for this course, please contact us to arrange.
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Introduction to Graph Computing

 28 Hours
In this instructor-led, live training in New York, 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 (also known as Graph Analytics) 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:
  • Understand how graph data is persisted and traversed.
  • Select the best framework for a given task (from graph databases to batch processing frameworks.)
  • Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
  • View real-world big data problems in terms of graphs, processes and traversals.
Read more...

Hadoop and Spark for Administrators

 35 Hours
This instructor-led, live training in New York (online or onsite) is aimed at system administrators who wish to learn how to set up, deploy and manage Hadoop clusters within their organization. By the end of this training, participants will be able to:
  • Install and configure Apache Hadoop.
  • Understand the four major components in the Hadoop ecoystem: HDFS, MapReduce, YARN, and Hadoop Common.
  • Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.  
  • Set up HDFS to operate as storage engine for on-premise Spark deployments.
  • Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
  • Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.
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Hortonworks Data Platform (HDP) for Administrators

 21 Hours
This instructor-led, live training in New York (online or onsite) introduces Hortonworks Data Platform (HDP) and walks participants through the deployment of Spark + Hadoop solution. By the end of this training, participants will be able to:
  • Use Hortonworks to reliably run Hadoop at a large scale.
  • Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
  • Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
  • Process different types of data, including structured, unstructured, in-motion, and at-rest.
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A Practical Introduction to Stream Processing

 21 Hours
In this instructor-led, live training in New York (onsite or remote), participants will learn how to set up 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:
  • Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
  • Understand and select the most appropriate framework for the job.
  • Process of data continuously, concurrently, and in a record-by-record fashion.
  • Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
  • Integrate the most appropriate stream processing library with enterprise applications and microservices.
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SMACK Stack for Data Science

 14 Hours
This instructor-led, live training in New York (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions. By the end of this training, participants will be able to:
  • Implement a data pipeline architecture for processing big data.
  • Develop a cluster infrastructure with Apache Mesos and Docker.
  • Analyze data with Spark and Scala.
  • Manage unstructured data with Apache Cassandra.
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Apache Spark Fundamentals

 21 Hours
This instructor-led, live training in New York (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.
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Apache Spark in the Cloud

 21 Hours
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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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
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Scaling Data Pipelines with Spark NLP

 14 Hours
This instructor-led, live training in New York (online or onsite) is aimed at data scientists and developers who wish to use Spark NLP, built on top of Apache Spark, to develop, implement, and scale natural language text processing models and pipelines. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building NLP pipelines with Spark NLP.
  • Understand the features, architecture, and benefits of using Spark NLP.
  • Use the pre-trained models available in Spark NLP to implement text processing.
  • Learn how to build, train, and scale Spark NLP models for production-grade projects.
  • Apply classification, inference, and sentiment analysis on real-world use cases (clinical data, customer behavior insights, etc.).
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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:
- to execute SQL queries.
- to read data from an existing Hive installation. 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:
  • Install and configure Spark SQL.
  • Perform data analysis using Spark SQL.
  • Query data sets in different formats.
  • Visualize data and query results.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
Read more...

Apache Spark MLlib

 35 Hours
MLlib is Spark’s machine learning (ML) library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs. It divides into two packages:
  • spark.mllib contains the original API built on top of RDDs.
  • spark.ml provides higher-level API built on top of DataFrames for constructing ML pipelines.
Audience This course is directed at engineers and developers seeking to utilize a built in Machine Library for Apache Spark
Read more...

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Testimonials (9)

A lot of practical examples, different ways to approach the same problem, and sometimes not so obvious tricks how to improve the current solution

Rafal - Nordea

Course - Apache Spark MLlib

The live examples

Ahmet Bolat - Accenture Industrial SS

Course - Python, Spark, and Hadoop for Big Data

very interactive...

Richard Langford

Course - SMACK Stack for Data Science

Sufficient hands on, trainer is knowledgable

Chris Tan

Course - A Practical Introduction to Stream Processing

Get to learn spark streaming , databricks and aws redshift

Lim Meng Tee - Jobstreet.com Shared Services Sdn. Bhd.

Course - Apache Spark in the Cloud

practice tasks

Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo

Course - Python and Spark for Big Data (PySpark)

The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.

Safar Alqahtani - Elm Information Security

Course - Big Data Analytics in Health

This is one of the best hands-on with exercises programming courses I have ever taken.

Laura Kahn

Course - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

Richard is very calm and methodical, with an analytic insight - exactly the qualities needed to present this sort of course.

Kieran Mac Kenna

Course - Spark for Developers

Upcoming Courses

Python and Spark for Big Data (PySpark)

2025-05-06 9:30 am
21 hours
PA, Philadelphia - International Plaza Dr Suite
$ 3330 (Online)
$ 4830 (Classroom)

Administration of Apache Spark

2025-05-26 9:30 am
35 hours
NY, Queens - Forest Hills Tower
$ 6757 (Online)
$ 9257 (Classroom)

Python and Spark for Big Data (PySpark)

2025-06-03 9:30 am
21 hours
NY, Staten Island - 1120 South Avenue
$ 3330 (Online)
$ 4830 (Classroom)

Hortonworks Data Platform (HDP) for Administrators

2025-06-17 9:30 am
21 hours
NY, Long Island - Bohemia
$ 4054 (Online)
$ 5554 (Classroom)

SMACK Stack for Data Science

2025-07-01 9:30 am
14 hours
PA, Pittsburgh - Penn Center East Monroeville
$ 3185 (Online)
$ 4185 (Classroom)

Introduction to Graph Computing

2025-07-15 9:30 am
28 hours
NY, Brooklyn - One Pierrepont Plaza
$ 5405 (Online)
$ 7405 (Classroom)

Python and Spark for Big Data (PySpark)

2025-07-29 9:30 am
21 hours
NY, Long Island - New Hyde Park
$ 3330 (Online)
$ 4830 (Classroom)

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