312 S 4th St Downtown, Suite 700, Louisville , United States, 40202
Louisville, KY – Regus at MET Building
The venue is located in the heart of downtown Louisville within the historic MET Building on Fourth Street, easily reachable by car via I‑64, I‑65, or I‑71, with several public parking garages nearby. From Louisville Muhammad Ali International Airport (SDF), approximately 12 miles southwest, a taxi or rideshare takes around 15–20 minutes via I‑65 North and Brook Street. Public transit is available via TARC buses with stops along Fourth and Broadway, and the building is within a five-minute walk from major bus routes—ideal for attendees arriving without a car.
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Administration of Apache Spark
35 HoursHadoop and Spark for Administrators
35 HoursPySpark & 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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