Azure Data Lake Storage Gen2 Training Course

This live, instructor-led training in Argentina (online or onsite) is designed for intermediate to advanced professionals aiming to build and deploy AI-powered cloud applications using Microsoft Azure.

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

• Develop event-driven and serverless applications using Azure Functions.
• Manage Azure storage solutions and virtual machines.
• Deploy and scale web applications using Azure App Service and Docker containers.
• Integrate AI, machine learning, and natural language processing using Azure AI Services.
• Leverage GitHub Copilot to assist in AI-driven cloud application development.

This course equips IT Professionals with the skills to manage Azure subscriptions, secure identities, administer infrastructure, configure virtual networking, link Azure with on-premises sites, manage network traffic, implement storage solutions, create and scale virtual machines, deploy web apps and containers, back up and share data, and monitor overall solution performance.

Designed for Azure Administrators, this content focuses on implementing, managing, and monitoring identity, governance, storage, compute, and virtual networks in a cloud environment. Azure Administrators will learn to provision, size, monitor, and adjust resources as needed.

This instructor-led, live training in Argentina (online or onsite) targets beginner, intermediate, and advanced developers and technical professionals who wish to use Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a functional agent, connect agents to business knowledge sources, and evaluate and prepare agents for deployment.

This instructor-led, live training in Argentina (online or onsite) is aimed at DevOps engineers, developers, and project managers who wish to utilize Azure DevOps to build and deploy optimized enterprise applications faster than traditional development approaches.

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

• Understand the fundamental DevOps vocabulary and principles.
• Install and configure the necessary Azure DevOps tools for software development.
• Utilize Azure DevOps tools and services to continuously adapt to the market.
• Build enterprise applications and evaluate current development processes upon Azure DevOps solutions.
• Manage teams more efficiently and accelerate software deployment time.
• Adopt DevOps development practices within the organization.

This instructor-led, live training in Argentina (online or onsite) is designed for intermediate-level data scientists and engineers who intend 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.

This instructor-led, live training in Argentina (online or onsite) is tailored for intermediate-level Java developers, software engineers, and cloud enthusiasts who wish to utilize Azure OpenAI to develop intelligent applications.

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

• Understand the fundamental principles of Generative AI and its applications.
• Set up and manage an Azure OpenAI service.
• Integrate OpenAI's models into Java applications.
• Deploy AI-powered features within web applications.

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

This instructor-led, live training in Argentina (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 Argentina (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 learning curve for Apache Spark can be steep at the outset, requiring significant effort before seeing initial results. This course is designed to help you overcome that initial hurdle. Upon completion, participants will grasp the fundamentals of Apache Spark, clearly distinguish between RDDs and DataFrames, and gain proficiency in both Python and Scala APIs. You will also learn about executors, tasks, and other core concepts. Adhering to best practices, the course places a strong emphasis on cloud deployment, specifically focusing on Databricks and AWS. Students will explore the differences between AWS EMR and AWS Glue, one of AWS's latest Spark-related services.

AUDIENCE:

Data Engineers, DevOps Professionals, Data Scientists

In this instructor-led, live training in Argentina, participants will learn how to combine Python and Spark to analyze big data while working through practical exercises.

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

• Utilize Spark with Python for big data analysis.
• Complete exercises that simulate real-world scenarios.
• Apply various tools and techniques for big data analysis using PySpark.

This instructor-led, live training in Argentina (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.

Stratio stands as a data-centric platform that seamlessly integrates big data, artificial intelligence, and governance into a unified 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 effectively utilize Stratio's Rocket and Intelligence modules with PySpark. The curriculum focuses on mastering looping structures, user-defined functions, and implementing sophisticated data logic.

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

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

Course Format

• Interactive lectures accompanied by guided discussions.
• Extensive exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request a customized training session for this course, please contact us to make arrangements.