Online or onsite, instructor-led live Apache Hadoop training courses demonstrate through interactive hands-on practice the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems.
Hadoop training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Michigan onsite live Hadoop trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Detroit, MI - Renaissance Center
400 Renaissance Center, Detroit, United States, 48243
The GM Renaissance Center is conveniently located in downtown Detroit and easily accessed by car via Interstates 75 or 94, with secure underground parking available on site. Travelers flying into Detroit Metropolitan Airport (DTW) can expect a 25–30 minute trip by taxi or rideshare via I‑94. Public transit is efficient: the Detroit People Mover stops directly at the Renaissance Center station, and DDOT routes 3 and 9 serve nearby Jefferson Avenue. Pedestrian skywalks provide safe indoor access from downtown hotels, parking garages, and the riverwalk.
Ann Arbor, MI – Regus - South State Commons I
2723 S State St, Ann Arbor, United States, 48104
Regus South State Commons I is conveniently located off I‑94 via Exit 177 (State Street), with easy access to downtown Ann Arbor and surrounding suburbs. The building offers free on-site surface parking for guests. From Detroit Metropolitan Airport (DTW), the venue can be reached in approximately 20–25 minutes by taxi or rideshare via I‑94 West. Local public transit service (TheRide) operates Route 24 along South State Street, with a stop within a short 2-minute walk of the building.
Grand Rapids, MI - Regus – Calder Plaza
250 Monroe Ave NW, Grand Rapids, United States, 49503
The venue sits centrally at 250 Monroe Avenue NW in downtown Grand Rapids, easily accessed by car via US‑131 or I‑196—with connections via Monroe or Ottawa exits—and offers shared underground and surface parking. From Gerald R. Ford International Airport, take I‑96 East then I‑196 West into the city; the drive is about 20 minutes. Public transit through Rapid bus routes stops near Monroe or Ottawa Avenue, just a short walk from the Regus entrance; the downtown area is pedestrian-friendly.
Lansing, MI - Regus - One Michigan Avenue
120 North Washington Square, Lansing, United States, 48933
The venue is located in the heart of Lansing’s central business district at 120 North Washington Square, easily accessible by car via I‑496 or US‑127 with convenient street parking and a nearby parking ramp. From Capital Region International Airport (LAN), the location is approximately a 12‑minute drive west via I‑96 and US‑127, with taxis and rideshares readily available. Public transit users can take CATA bus routes that stop just a block away on Washington or Grand Avenue, offering seamless access to the venue.
This instructor-led, live training in Michigan (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.
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.
Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. In this three (optionally, four) days course, attendees will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan cluster deployment and growth, how to install, maintain, monitor, troubleshoot and optimize Hadoop. They will also practice cluster bulk data load, get familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course finishes off with discussion of securing cluster with Kerberos.
“…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized”
— Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising
Audience
Hadoop administrators
Format
Lectures and hands-on labs, approximate balance 60% lectures, 40% labs.
Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop ecosystem.
Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase. These advanced programming techniques will be beneficial to experienced Hadoop developers.
This instructor-led, live training in Michigan (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.
This course introduces HBase – a NoSQL store on top of Hadoop. The course is intended for developers who will be using HBase to develop applications, and administrators who will manage HBase clusters.
We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course is very hands-on with lots of lab exercises.
This instructor-led, live training in Michigan (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.
Cloudera Impala is an open source massively parallel processing (MPP) SQL query engine for Apache Hadoop clusters.
Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache Hbase without requiring data movement or transformation.
Audience
This course is aimed at analysts and data scientists performing analysis on data stored in Hadoop via Business Intelligence or SQL tools.
After this course delegates will be able to
Extract meaningful information from Hadoop clusters with Impala.
Write specific programs to facilitate Business Intelligence in Impala SQL Dialect.
In this instructor-led, live training in Michigan (onsite or remote), participants will learn how to deploy and manage Apache NiFi in a live lab environment.
By the end of this training, participants will be able to:
Install and configure Apachi NiFi.
Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes.
In this instructor-led, live training in Michigan, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi.
By the end of this training, participants will be able to:
Understand NiFi's architecture and dataflow concepts.
Develop extensions using NiFi and third-party APIs.
Custom develop their own Apache Nifi processor.
Ingest and process real-time data from disparate and uncommon file formats and data sources.
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Testimonials (8)
The live examples
Ahmet Bolat - Accenture Industrial SS
Course - Python, Spark, and Hadoop for Big Data
During the exercises, James explained me every step whereever I was getting stuck in more detail. I was completely new to NIFI. He explained the actual purpose of NIFI, even the basics such as open source. He covered every concept of Nifi starting from Beginner Level to Developer Level.
Firdous Hashim Ali - MOD A BLOCK
Course - Apache NiFi for Administrators
Trainer's preparation & organization, and quality of materials provided on github.
Mateusz Rek - MicroStrategy Poland Sp. z o.o.
Course - Impala for Business Intelligence
That I had it in the first place.
Peter Scales - CACI Ltd
Course - Apache NiFi for Developers
practical things of doing, also theory was served good by Ajay
Dominik Mazur - Capgemini Polska Sp. z o.o.
Course - Hadoop Administration on MapR
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
Liked very much the interactive way of learning.
Luigi Loiacono
Course - Data Analysis with Hive/HiveQL
I mostly liked the trainer giving real live Examples.
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