Online or onsite, instructor-led live Apache Spark training courses demonstrate through hands-on practice how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis.
Apache Spark 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. Onsite live Apache Spark trainings in Salvador can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Salvador-Suarez Trade
Av. Tancredo Neves, 450 - Caminho das Árvores, Salvador, Brazil, 41819-900
The Salvador Suarez Trade Center office space is situated on the 16th floor of a 34-story granite blue glass skyscraper, located on a main road through the financial district. Salvador is the second most popular tourist destination in Brazil. National and international real estate developers are investing in the expansion of the city, and construction is one of the most important commercial activities. The city is also attracting major global companies, creating oil plants, car factories and chemicals near Salvador. The port plays a key role in local trade, especially for the transport of agricultural products from the surrounding region. The city is popular for conferences. Salvador Suarez Trade Center has a fully equipped auditorium, a lan house and its own parking lot, and is near one of the city's main shopping centers. You can easily reach the international airport and other transport links.
Salvador - Mundo Plaza Centre
Avenue Tancredo Neves, 620 , Salvador , Brazil, 41820-901
Discover the ideal headquarters in this city, known for its business opportunities and as a sought-after tourist spot. Nestled in one of the most vibrant neighborhoods, the recently constructed Mundo Plaza Centre seamlessly blends modern architecture with lush greenery, providing you with an appealing work setting.
Be inspired by the stunning vistas from this airy and expansive office space. And after a productive day, immerse yourself in the finest accommodations, boutiques, and cultural offerings that Salvador has to offer.
This instructor-led, live training in Salvador (online or onsite) targets intermediate-level data scientists and engineers who wish to utilize Google Colab and Apache Spark for big data processing and analytics.
By the conclusion 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.
Stratio is a data-centric platform that combines big data, artificial intelligence, and governance into a unified solution. Its Rocket and Intelligence modules facilitate rapid data exploration, transformation, and advanced analytics within enterprise environments.
This instructor-led live training (available online or onsite) is designed for intermediate-level data professionals seeking to effectively utilize the Rocket and Intelligence modules in Stratio with PySpark. The course focuses on looping structures, user-defined functions, and advanced data logic.
Upon completing this training, participants will be able to:
Navigate and operate within the Stratio platform using the Rocket and Intelligence modules.
Apply PySpark for data ingestion, transformation, and analysis.
Utilize loops and conditional logic to manage data workflows and perform feature engineering.
Create and manage user-defined functions (UDFs) to enable reusable data operations in PySpark.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical activities.
Hands-on implementation in a live laboratory environment.
Course Customization Options
To request customized training for this course, please contact us to make arrangements.
This instructor-led, live training in Salvador (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.
This instructor-led live training in Salvador (online or onsite) is aimed at beginner to intermediate 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.
In this instructor-led, live training in Salvador, 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.
This training offers a hands-on introduction to creating scalable data processing and Machine Learning workflows using PySpark. Participants will gain insight into how Apache Spark functions within contemporary Big Data ecosystems and how to efficiently manage large datasets by leveraging distributed computing principles.
This instructor-led, live training in Salvador (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.
The learning curve for Apache Spark can be steep at the beginning, requiring considerable effort to see initial results. This course is designed to help you navigate those early challenges effectively. Upon completion, participants will grasp the fundamentals of Apache Spark, clearly distinguish between RDDs and DataFrames, and become proficient with the Python and Scala APIs. You will also gain insights into how executors and tasks operate. Aligned with industry best practices, the course places a strong emphasis on cloud deployment, specifically focusing on Databricks and AWS environments. Additionally, students will learn to differentiate between AWS EMR and AWS Glue, exploring one of AWS's newer Spark services.
AUDIENCE:
Data Engineers, DevOps Professionals, Data Scientists
Spark SQL serves as Apache Spark's dedicated module for handling structured and unstructured data. It provides insights into the data's structure alongside the computations being executed, enabling the system to implement various optimizations. Spark SQL is commonly utilized for two main purposes:
- Executing SQL queries.
- Accessing data from an existing Hive installation.
Through this instructor-led live training, available either onsite or remotely, participants will acquire the skills necessary to analyze diverse datasets using Spark SQL.
Upon completing this training, participants will be equipped to:
Install and configure Spark SQL.
Conduct data analysis using Spark SQL.
Query datasets across various formats.
Visualize data and the results of queries.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical practice.
Hands-on implementation within a live-lab environment.
Customization Options
To arrange a customized training session for this course, please contact us.
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Testimonials (3)
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
Having hands on session / assignments
Poornima Chenthamarakshan - Intelligent Medical Objects
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