MN, Minneapolis - Fifth Street Towers

100 S 5th St, 19th Floor, Minneapolis, United States, 55402

The venue is located in the heart of downtown Minneapolis at Fifth Street Towers, easily accessed by car via I‑94 or I‑35W with exits to S 5th St; paid underground parking is available in the building garage. From Minneapolis–Saint Paul International Airport (MSP), take I‑494 North to I‑35W North, then exit at 5th Street—taxi or rideshare takes around 20 minutes. Public transit users can arrive via the METRO light rail to Nicollet Mall Station or by several bus routes that stop on 5th Street, with the entrance a brief walk from public transit.

Eagan, MN - Grand Oak I

860 Blue Gentian Rd, Ste 200, Eagen, United States, 55121

The venue is located in the Grand Oak Business Park at 860 Blue Gentian Road, easily accessed by car via I‑494 and Highway 55; ample on-site parking makes arrival simple. From Minneapolis–Saint Paul International Airport (MSP), it’s about a 5‑minute drive—take I‑494 East and exit at Blue Gentian Road. Public transit users can take Metro Transit bus routes to a stop near Blue Gentian Road and walk a few minutes from there.

Subcategories (1)

PySpark

PySpark

Explore Our Courses

Big Data Analytics with Google Colab and Apache Spark

 14 Hours

This instructor-led, live training in Minnesota (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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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.
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Python, Spark, and Hadoop for Big Data

 21 Hours

This instructor-led, live training in Minnesota (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 Minnesota (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 Minnesota, 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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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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Hadoop and Spark for Administrators

 35 Hours

This instructor-led, live training in Minnesota (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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A Practical Introduction to Stream Processing

 21 Hours

In this instructor-led, live training in Minnesota (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 Minnesota (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 Minnesota (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 Minnesota (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...

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Testimonials (7)

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

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

Stratio: Rocket and Intelligence Modules with PySpark

2025-11-12 9:30 am
14 hours
MN, Minneapolis - Fifth Street Towers
$ 2703 (Online)
$ 3703 (Classroom)

Big Data Analytics in Health

2025-11-26 9:30 am
21 hours
MN, Minneapolis - Fifth Street Towers
$ 4054 (Online)
$ 5554 (Classroom)

A Practical Introduction to Stream Processing

2025-12-10 9:30 am
21 hours
MN, Minneapolis - Fifth Street Towers
$ 4054 (Online)
$ 5554 (Classroom)

Scaling Data Pipelines with Spark NLP

2025-12-24 9:30 am
14 hours
MN, Minneapolis - Fifth Street Towers
$ 2703 (Online)
$ 3703 (Classroom)

SMACK Stack for Data Science

2026-01-07 9:30 am
14 hours
MN, Minneapolis - Fifth Street Towers
$ 3185 (Online)
$ 4185 (Classroom)

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