Houston, TX - Regus – Downtown at Pennzoil Place

700 Milam Street, Suite 1300, Houston, United States, 77002

The venue is centrally located near major highways, including I‑45, I‑69, and US‑59, with convenient parking available in the building’s garage as well as nearby garages. For those arriving by air, both George Bush Intercontinental Airport (IAH) and William P. Hobby Airport (HOU) are just 7 to 10 miles away. Public transit is easily accessible via METRO bus routes, and the venue also offers tunnel access to downtown amenities.

Dallas, TX - Regus - Downtown Republic Center

325 N. St. Paul Street, Dallas, United States, 75201

The venue is conveniently located in downtown Dallas and easily accessible by car via I‑35E, US‑75, and I‑30, with several parking garages and surface lots nearby. Public transit access is excellent, just steps from St. Paul Station on the DART Blue and Red lines and connected to the downtown tunnel network. For those arriving by air, Dallas Love Field is approximately 7 miles away, while DFW International Airport is about 20 miles from the venue. Valet service is available at the building, along with multiple nearby parking options.

Austin, TX - Regus - Lamar Central

3800 N Lamar Blvd, Suite 200, Austin, United States, 78756

Easily reachable by car via Mopac (Loop 1) and US‑183. Plenty of nearby public parking is available. For air travelers, Austin-Bergstrom International Airport (AUS) is approximately 10 miles away. Local transit access is provided via bus routes serving Lamar Blvd.

Austin, TX – Regus at Dobie Center

2021 Guadalupe Street, Suite 260, Austin, United States, 78705

The venue is located in the vibrant West Campus neighborhood near the University of Texas at the Dobie Center, easily reachable by car via I‑35 or I‑35 Frontage Road and Loop 1, with on-site and street parking nearby. From Austin–Bergstrom International Airport (AUS), about 11 miles southeast, a taxi or rideshare takes around 20–25 minutes via TX‑71 West and I‑35 North. Public transit users can take Capital Metro routes to the University of Texas/Dobie Mall stop directly in front of the building, placing it within a short walk for attendees without cars.

Lubbock, TX

1610 Broadway, Lubbock, United States, 79401

The venue is conveniently located just off I‑27, offering easy access by car with on-site self-parking and nearby garages. For those arriving by air, Fort Smith Regional Airport is approximately 6 miles away, providing quick and convenient access. Public transit is also available, with downtown bus routes serving the area and the venue within walking distance of central Lubbock locations.
NobleProg Training Place, City Dallas, TX - Uptown

Dallas, TX - Uptown

3232 McKinney Ave, Dallas, United States, 75204

The venue is located at 3232 McKinney Avenue in the heart of Uptown Dallas, a walkable and transit-oriented district just north of Downtown. It’s easily accessible by car via US‑75 (Central Expressway), Spur 366 (Woodall Rodgers), or I‑345 with adjacent parking garages and street parking. From Dallas/Fort Worth International Airport (DFW), taxis or rideshares take about 25–30 minutes via TX‑121 South and US‑75 South. From Dallas Love Field (DAL), it's a quick 15‑minute ride via Harry Hines Blvd and Herb Kelleher Way. Public transit options include the McKinney Ave Trolley stop directly outside and DART Light Rail nearby—making it convenient even without a vehicle.

Houston, TX – Regus at Capital One Building

5444 Westheimer Rd Uptown, Suite 1000, Houston, United States, 77056

The venue is located in the Capital One Building off Westheimer Road in the Galleria/Uptown area, easily accessed by car via I‑610, US‑59, or Westheimer, with ample attached covered parking and visitor spaces on-site. From Houston’s George Bush Intercontinental Airport (IAH), a taxi or rideshare takes approximately 25–30 minutes via I‑69 South and I‑610 West. From William P. Hobby Airport (HOU), the ride takes about 35 minutes via I‑45 North and I‑610 West. Public transit is served by Metro bus routes along Westheimer Drive with stops close to the building, enabling easy access for attendees without cars.

Austin, TX - Regus - Littlefield Congress

106 E 6th St, Austin, United States, 78701

The venue is conveniently situated near I‑35 and US‑183, making it easily accessible by car, with both public and garage parking options—such as the Littlefield Garage at 508 Brazos—located within walking distance. For those using public transportation, the venue is just a short walk from the Downtown Station (CapMetro) and is served by several bus routes. Travelers arriving by air will find that Austin-Bergstrom International Airport is approximately 8 miles away, providing straightforward access to and from the venue.

San Antonio, TX - Regus - One Riverwalk Place

700 North Saint Mary's Street, One Riverwalk Place, Ste 1400, San Antonio, United States, 78205

The venue is easily accessible by car via major highways including I‑35, I‑37, and I‑10, with the convenience of an on-site parking garage and nearby public lots. For those traveling by air, San Antonio International Airport (SAT) is located approximately 8 miles away. Public transit options are also readily available, with several bus lines nearby and the downtown VIA Transit hub just a short walk from the building.

San Antonio, TX – Venture X at River Walk

500 Navarro St, San Antonio, United States, 78205

The venue sits on the second floor of a historic building at 500 Navarro Street, steps from the iconic River Walk. It’s easily reached by car via I‑10, I‑35, or US‑281, with public parking available in a ten-story garage across the street and additional on‑street spots. From San Antonio International Airport (SAT), a taxi or rideshare takes about 13 minutes via I‑410 Inner Loop and I‑35 North. Public transit options include VIA bus routes and the River Walk shuttle with stops near Navarro, making the location highly accessible for attendees without cars.

Subcategories (3)

GraphX

GraphX
Apache Spark MLlib

Apache Spark MLlib
PySpark

PySpark

Explore Our Courses

Big Data Analytics with Google Colab and Apache Spark

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This instructor-led, live training in Texas (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.
Read more...

Stratio: Rocket and Intelligence Modules with PySpark

 14 Hours

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 Customization Options

  • To request a customized training for this course, please contact us to arrange.
Read more...

Python, Spark, and Hadoop for Big Data

 21 Hours

This instructor-led, live training in Texas (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

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This instructor-led, live training in Texas (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.
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Python and Spark for Big Data (PySpark)

 21 Hours

In this instructor-led, live training in Texas, 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

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This course is aimed at developers and data scientists who wish to understand and implement artificial intelligence in their applications. Special focus will be given to data analysis, distributed artificial intelligence, 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.
Read more...

Introduction to Graph Computing

 28 Hours

In this instructor-led, live training in Texas, 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.
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Hadoop and Spark for Administrators

 35 Hours

This instructor-led, live training in Texas (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 Texas (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 Texas (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 Texas (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 Texas (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 Texas (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, Spark, and Hadoop for Big Data

2025-09-22 9:30 am
21 hours
Austin, TX - Regus - Lamar Central
$ 4054 (Online)
$ 4654 (Classroom)

Apache Spark SQL

2025-10-06 9:30 am
7 hours
Lubbock, TX
$ 1630 (Online)
$ 1630 (Classroom)

Apache Spark MLlib

2025-10-20 9:30 am
35 hours
Austin, TX - Regus - Lamar Central
$ 6757 (Online)
$ 7757 (Classroom)

Administration of Apache Spark

2025-11-03 9:30 am
35 hours
Lubbock, TX
$ 6757 (Online)
$ 6757 (Classroom)

Administration of Apache Spark

2025-11-17 9:30 am
35 hours
Austin, TX - Regus - Lamar Central
$ 6757 (Online)
$ 7757 (Classroom)

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