Python, Spark, and Hadoop for Big Data Training Course

This instructor-led, live training in Vietnam (online or onsite) is aimed at intermediate-level data scientists and engineers who wish to use 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.

Apache NiFi is an open-source, flow-based data integration and event-processing platform. It enables automated, real-time data routing, transformation, and system mediation between disparate systems, with a web-based UI and fine-grained control.

This instructor-led, live training (onsite or remote) is aimed at intermediate-level administrators and engineers who wish to deploy, manage, secure, and optimize NiFi dataflows in production environments.

By the end of this training, participants will be able to:

• Install, configure, and maintain Apache NiFi clusters.
• Design and manage dataflows from varied sources and sinks.
• Implement flow automation, routing, and transformation logic.
• Optimize performance, monitor operations, and troubleshoot issues.

Format of the Course

• Interactive lecture with real-world architecture discussion.
• Hands-on labs: building, deploying, and managing flows.
• Scenario-based exercises in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This course offers a hands-on introduction to constructing scalable data processing and Machine Learning workflows using PySpark. Participants will gain insight into how Apache Spark functions within contemporary Big Data ecosystems and learn to efficiently manage large datasets by applying distributed computing principles.

This instructor-led, live training in Vietnam (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.

This instructor-led live training in Vietnam (online or onsite) is designed for 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.
• Debug and troubleshoot common Spark issues.

The initial learning curve for Apache Spark can be steep, requiring significant effort before seeing tangible results. This course is designed to help learners quickly overcome that initial hurdle. Upon completion, participants will gain a solid understanding of Apache Spark's fundamentals, clearly distinguishing between RDDs and DataFrames. They will become proficient in both Python and Scala APIs, comprehend how executors and tasks function, and more. Additionally, aligning with industry best practices, the curriculum places a strong emphasis on cloud deployment strategies, specifically focusing on Databricks and AWS. Students will also explore the distinctions between AWS EMR and AWS Glue, one of AWS's latest Spark-based services.

AUDIENCE:

Data Engineers, DevOps Professionals, Data Scientists

In this instructor-led, live training in Vietnam, 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.

Stratio offers a unified platform that combines big data capabilities, artificial intelligence, and governance. Its Rocket and Intelligence modules facilitate swift data exploration, transformation, and advanced analytics within enterprise settings.

This instructor-led live training (available online or onsite) is designed for intermediate-level data professionals aiming to effectively utilize Stratio's Rocket and Intelligence modules with PySpark. The curriculum emphasizes looping structures, user-defined functions, and complex data logic.

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

• Navigate the Stratio platform proficiently using its Rocket and Intelligence modules.
• Apply PySpark for data ingestion, transformation, and analysis tasks.
• Utilize loops and conditional logic to manage data workflows and feature engineering processes.
• Develop and manage user-defined functions (UDFs) to enable reusable data operations in PySpark.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical applications.
• Hands-on implementation in a live laboratory environment.

Customization Options

• For customized training needs, please contact us to make arrangements.