Apache Spark Training in Ankara

This instructor-led live training in Ankara (online or onsite) is tailored for intermediate-level data scientists and engineers who want to utilize Google Colab and Apache Spark for big data processing and analytics.

By the end 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.
• Integrate Apache Spark with cloud-based tools.

Stratio is a comprehensive, data-centric platform that unifies big data capabilities, artificial intelligence, and governance into a single cohesive solution. Its Rocket and Intelligence modules empower organizations to perform rapid data exploration, transformation, and advanced analytics within enterprise environments.

This instructor-led live training, available both online and onsite, is designed for intermediate-level data professionals aiming to master the Rocket and Intelligence modules in Stratio using PySpark. The curriculum emphasizes looping structures, user-defined functions, and sophisticated data logic.

Upon completion of this training, participants will be able to:

• Navigate and operate effectively within the Stratio platform utilizing the Rocket and Intelligence modules.
• Apply PySpark techniques for data ingestion, transformation, and analysis.
• Utilize loops and conditional logic to manage data workflows and execute feature engineering tasks.
• Create and manage user-defined functions (UDFs) to facilitate reusable data operations within PySpark.

Course Format

• Interactive lectures paired with group discussions.
• Extensive exercises and practical application sessions.
• Hands-on implementation within a live-lab environment.

Customization Options

• For organizations seeking customized training for this course, please contact us to arrange a tailored program.

This instructor-led, live training in Ankara (online or onsite) is designed for developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex datasets.

Upon completion of this training, participants will be able to:

• Configure the necessary environment to begin processing big data using Spark, Hadoop, and Python.
• Gain a comprehensive understanding of the features, core components, and architecture of Spark and Hadoop.
• Master the integration of Spark, Hadoop, and Python for efficient big data processing.
• Explore key tools within the Spark ecosystem, including Spark MLlib, Spark Streaming, Kafka, Sqoop, and Flume.
• Develop collaborative filtering recommendation systems akin to those used by Netflix, YouTube, Amazon, Spotify, and Google.
• Utilize Apache Mahout to scale machine learning algorithms.

This instructor-led, live training in Ankara (online or onsite) targets beginner to intermediate system administrators seeking to deploy, maintain, and optimize Spark clusters.

Upon completion of this training, participants will be able to:

• Install and configure Apache Spark across diverse environments.
• Manage cluster resources and oversee Spark applications.
• Enhance the performance of Spark clusters.
• Implement security protocols and ensure high availability.
• Debug and resolve common Spark issues.

In this instructor-led, live training in Ankara, 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 course offers a hands-on introduction to creating scalable data processing and Machine Learning workflows with PySpark. Attendees will explore how Apache Spark functions within contemporary Big Data ecosystems and learn to efficiently process extensive datasets using distributed computing principles.

This instructor-led live training in Ankara (online or onsite) is aimed at engineers who wish to set up and deploy an 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.

Although the initial learning curve for Apache Spark can be steep, requiring significant effort to see results, this course is designed to help you navigate that challenging phase quickly. Upon completion, participants will grasp the fundamentals of Apache Spark, clearly distinguish between RDDs and DataFrames, and master both the Python and Scala APIs. You will also gain a deep understanding of executors, tasks, and other core concepts. Aligned with industry best practices, the curriculum places strong emphasis on cloud deployment, particularly within Databricks and AWS environments. Students will learn to differentiate between AWS EMR and AWS Glue, one of AWS’s latest Spark services.

AUDIENCE:

Data Engineers, DevOps Professionals, Data Scientists