1426 North 3rd Street, 4th Floor, Harrisburg, United States, 17102
Harrisburg, PA – Regus at Campus Square
The venue is situated in the modern LEED Gold–certified Campus Square building at 1426 N 3rd Street in Midtown Harrisburg, easily reachable by car via I‑83 or Route 230, with ample on-site parking and nearby municipal garages. From Harrisburg International Airport (MDT), about 12 miles southwest, a taxi or rideshare typically takes 15–20 minutes via PA‑283 West and I‑83 North. Public transit is convenient: several Capital Area Transit buses stop within a block, and the building is within walking distance of major routes and complemented by Midtown’s walkable environment and local amenities.
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Explore Our Courses
Administration of Apache Spark
35 HoursHadoop and Spark for Administrators
35 HoursPySpark and Machine Learning
21 HoursSMACK Stack for Data Science
14 HoursApache Spark Fundamentals
21 HoursApache Spark in the Cloud
21 HoursSpark for Developers
21 HoursApache Spark SQL
7 HoursLast Updated:
Testimonials (6)
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
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.
Raul Mihail Rat - 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
Having hands on session / assignments
Poornima Chenthamarakshan - Intelligent Medical Objects
Course - Apache Spark in the Cloud
Doing similar exercises different ways really help understanding what each component (Hadoop/Spark, standalone/cluster) can do on its own and together. It gave me ideas on how I should test my application on my local machine when I develop vs when it is deployed on a cluster.
Thomas Carcaud - IT Frankfurt GmbH
Course - Spark for Developers
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