For government agencies, instructor-led live Apache Spark training courses are available both online and onsite. These courses provide hands-on practice to demonstrate how Spark integrates into the Big Data ecosystem and how it can be effectively used for data analysis.
Apache Spark training is offered in two formats: "online live training" or "onsite live training." Online live training, also known as "remote live training," is conducted via an interactive remote desktop. Onsite live training can be arranged at customer premises in Fayetteville or at NobleProg corporate training centers in Fayetteville.
NobleProg -- Your Local Training Provider for government agencies and organizations.
Fayetteville, AR - The Root
3537 N Steele Blvd Ste. 110, Fayetteville, United States, 72703
Easily accessible from I‑49 via Steele Boulevard exit. The venue is located on Fayetteville Square with street and nearby garage parking. Northwest Arkansas Regional Airport (XNA) is approximately 15 miles away. Attendees can also use local bus routes serving downtown.
This instructor-led, live training (available online or onsite) is designed for intermediate-level data scientists and engineers who wish to utilize Google Colab and Apache Spark for big data processing and analytics.
By the end of this training, participants will be able to:
- Configure a big data environment using Google Colab and Apache Spark.
- Efficiently process and analyze large datasets with Apache Spark.
- Visualize big data in a collaborative setting.
- Integrate Apache Spark with cloud-based tools for government.
Stratio is a data-centric platform that integrates big data, AI, and governance into a single solution. Its Rocket and Intelligence modules facilitate rapid data exploration, transformation, and advanced analytics in enterprise environments.
This instructor-led, live training (online or onsite) is designed for intermediate-level data professionals who aim to effectively utilize the Rocket and Intelligence modules in Stratio 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 the Rocket and Intelligence modules.
- Apply PySpark for 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.
- Extensive exercises and practice sessions.
- Hands-on implementation in a live-lab environment.
**Course Customization Options for Government**
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Fayetteville (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 for government.
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 efficient big data processing.
- Explore tools in the Spark ecosystem, including Spark MlLib, Spark Streaming, Kafka, Sqoop, Flume, and others.
- Build collaborative filtering recommendation systems similar to those used by Netflix, YouTube, Amazon, Spotify, and Google.
- Use Apache Mahout to scale machine learning algorithms for government applications.
This instructor-led, live training in Fayetteville (online or onsite) is designed for beginner to intermediate-level system administrators who aim to deploy, maintain, and optimize Spark clusters for government use.
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 effectively.
- Optimize the performance of Spark clusters to meet operational requirements.
- Implement security measures and ensure high availability for government systems.
- Debug and troubleshoot common issues that may arise in Spark deployments.
In this instructor-led, live training in [location], participants will learn how to leverage Python and Spark together to analyze large datasets as they engage in hands-on exercises.
By the end of this training, participants will be able to:
- Utilize Spark with Python for comprehensive big data analysis.
- Engage in exercises that simulate real-world scenarios.
- Apply various tools and techniques for big data analysis using PySpark, enhancing their capabilities for government projects.
This instructor-led, live training in Fayetteville (online or onsite) is aimed at system administrators who wish to learn how to set up, deploy, and manage Hadoop clusters within their organization for government use.
By the end of this training, participants will be able to:
- Install and configure Apache Hadoop.
- Understand the four major components in the Hadoop ecosystem: 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 a storage engine for on-premise Spark deployments.
- Configure Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems like Redis, Elasticsearch, Couchbase, Aerospike, etc.
- Perform administrative tasks such as provisioning, management, monitoring, and securing an Apache Hadoop cluster.
In this instructor-led, live training in Fayetteville (onsite or remote), participants will learn how to set up and integrate various Stream Processing frameworks with existing big data storage systems and related software applications and microservices for government.
By the end of this training, participants will be able to:
- Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streams.
- Understand and select the most appropriate framework for specific tasks.
- Process data continuously, concurrently, and on a record-by-record basis.
- Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc., ensuring seamless integration within government systems.
- Choose and integrate the most suitable stream processing library with enterprise applications and microservices for government.
Python is a high-level programming language renowned for its clear syntax and code readability. Apache Spark is a powerful data processing engine utilized for querying, analyzing, and transforming large datasets. PySpark facilitates the integration of Spark with Python, enabling seamless data processing workflows.
Target Audience: Intermediate-level professionals in the banking sector who are familiar with Python and Spark and aim to enhance their expertise in big data processing and machine learning techniques, specifically for government and private sector applications.
This instructor-led, live training in Fayetteville (online or onsite) is aimed at data scientists who wish to utilize the SMACK stack to develop robust data processing platforms for government.
By the end of this training, participants will be able to:
- Implement a data pipeline architecture suitable for processing large-scale data.
- Develop a cluster infrastructure using Apache Mesos and Docker.
- Analyze data effectively with Spark and Scala.
- Manage unstructured data efficiently with Apache Cassandra.
This instructor-led, live training in Fayetteville (online or onsite) is aimed at engineers who wish to set up and deploy the 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.
- Efficiently process and analyze extensive datasets.
- Understand the distinctions between Apache Spark and Hadoop MapReduce, and determine which is more suitable for specific tasks.
- Integrate Apache Spark with other machine learning tools to enhance data processing capabilities for government applications.
Apache Spark has a steep initial learning curve that requires significant effort to overcome before yielding tangible results. This course is designed to help participants navigate this challenging first phase. Upon completion of the course, attendees will have a solid understanding of Apache Spark fundamentals, including the distinction between RDD and DataFrame, proficiency in using Python and Scala APIs, and knowledge of executors and tasks.
The curriculum emphasizes best practices, with a strong focus on cloud deployment, particularly through platforms such as Databricks and AWS. Participants will also gain insights into the differences between AWS EMR and AWS Glue, one of AWS's latest Spark services. This training is tailored for government data engineers, DevOps professionals, and data scientists to enhance their capabilities in leveraging Apache Spark for government projects.
This course will introduce Apache Spark, focusing on its integration into the Big Data ecosystem and its application for data analysis. Participants will learn how to utilize the Spark shell for interactive data analysis, understand Spark internals, and work with Spark APIs, Spark SQL, Spark streaming, machine learning, and GraphX.
This instructor-led, live training in [location] (online or onsite) is designed for government data scientists and developers who wish to utilize 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 for government projects.
- Understand the features, architecture, and benefits of using Spark NLP in a public sector context.
- Utilize the pre-trained models available in Spark NLP to implement text processing solutions tailored to government needs.
- Learn how to build, train, and scale Spark NLP models for production-grade projects within government agencies.
- Apply classification, inference, and sentiment analysis on real-world use cases relevant to government operations (such as public health data, citizen feedback, etc.).
Spark SQL is the Apache Spark module designed for handling structured and unstructured data. It provides metadata about the structure of the data and the computations being executed, which can be leveraged for performance optimizations. Two primary applications of Spark SQL include:
Executing SQL queries.
Reading data from an existing Hive installation.
In this instructor-led, live training (on-site or remote), participants will learn how to analyze various types of datasets using Spark SQL for government applications.
By the end of this training, participants will be able to:
Install and configure Spark SQL.
Conduct data analysis using Spark SQL.
Query datasets in different formats.
Visualize data and query results for government reporting and decision-making.
Format of the Course
Interactive lecture and discussion tailored to public sector workflows.
Extensive exercises and practice sessions.
Hands-on implementation in a live-lab environment, aligned with government standards and accountability measures.
Course Customization Options
To request a customized training for this course, tailored to specific government needs, please contact us to arrange.
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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.
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