Octave not only for programmers Training Course

This instructor-led, live training in Guatemala (online or onsite) is aimed at business analysts who wish to learn advanced Spotfire Analyst techniques for analyzing data.

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

• Share visualizations among different team members.
• Secure access to software based on roles and access controls.
• Create visualizations such as map charts.
• Integrate statistical computing languages such as R with Spotfire.

This instructor-led, live training in Guatemala (online or onsite) is aimed at business analysts and data analysts who wish to learn basic Spotfire Analyst techniques for analyzing data.

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

• Install and configure TIBCO Spotfire.
• Combine data from different databases.
• Visualize large datasets.
• Create and share complex dashboards.

This instructor-led, live training in Guatemala (online or onsite) is aimed at business analysts and data analysts who wish to use TIBCO Spotfire X with its artificial intelligence capabilities to visualize, transform, and analyze data.

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

• Install and configure TIBCO Spotfire X.
• Understand the features and architecture of TIBCO Spotfire X.
• Understand the concepts behind augmented and predictive analytics.
• Learn how to load, process, and visualize data using Spotfire X.
• Create interactive and enhanced data visualizations.

In this instructor-led, live training in Guatemala, participants will learn three different approaches for accessing, analyzing and visualizing data. We start with an introduction to RDMS databases; the focus will be on accessing and querying an Oracle database using the SQL language. Then we look at strategies for accessing an RDMS database programmatically using the Python language. Finally, we look at how to visualize and present data graphically using TIBCO Spotfire. 

Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.

This instructor-led, live training in Guatemala (online or onsite) is aimed at developers who wish to use BusinessEvents and ActiveMatrix Service Bus to develop, deploy, and manage event driven applications.

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

• Set up the necessary development environment to start developing.
• Build distributed, stateful, rule-based event-processing systems.
• Manage business events data and execute proper business rules.
• Reduce the event response time in large-scale, data driven applications.
• Build applications for fraud detection, track-and-trace, real-time customer offer generation, etc.

This instructor-led, live training in Guatemala (online or onsite) is aimed at engineers, researchers, and data analysts who wish to use TIBCO Statistica features to create analytic workflows and models.

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

• Install and navigate the TIBCO Statistica program to build and manage data analysis projects.
• Understand statistics basics to analyze data and generate useful insights for the business.
• Explore advanced topics to work with big data and machine learning using TIBCO Statistica.

This instructor-led, live training in Guatemala (onsite or remote) is aimed at data analysts who wish to use Grafana for monitoring and visualizing data.

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

• Set up the necessary development environment to start creating visualizations in Grafana.
• Set up Grafana for high availability.
• Customize panels and dashboards with data.
• Configure a reverse proxy for fast loading speeds.

This instructor-led, live training in Guatemala (online or onsite) is aimed at intermediate-level data analysts who wish to learn and utilize the advanced features and components of Grafana for data visualization and analysis.

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

• Gain an in-depth understanding of advanced Grafana concepts and components.
• Leverage template variables and dynamic dashboards for enhanced data visualization.
• Use Grafana Query Language for complex queries.
• Learn best practices for scaling Grafana, optimizing performance, and ensuring high availability.

This instructor-led, live training in Guatemala (online or onsite) is aimed at beginner to intermediate-level IT professionals who wish to gain the knowledge and practical skills necessary to excel in the administration of Grafana and GLPI.

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

• Create and customize Grafana dashboards with different visualizations.
• Implement alerting and notifications for monitoring.
• Administer user accounts, teams, and permissions.
• Manage IT assets effectively, including hardware and software inventory.
• Implement a helpdesk system for user support and ticket management.

This instructor-led, live training in Guatemala (online or onsite) is aimed at web developers and DevOps engineers who wish to visualize and monitor data with Grafana and Graphite.

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

• Aggregate and visualize metrics about systems and applications.
• Create a StatsD client for gathering application metrics.
• Build informative and dynamic dashboards with Grafana.
• Gather insights from back-end performance.

This instructor-led, live training in Guatemala (online or onsite) is aimed at intermediate-level administrators and developers who wish to deepen their understanding of Elasticsearch administration, including advanced techniques for dashboard development in Kibana, as well as maintenance of the system.

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

• Set up and configure Elasticsearch and Kibana environments for advanced administration and dashboard development.
• Create and manage Elasticsearch indices, mappings, and data models.
• Develop advanced queries and filters to extract valuable insights from Elasticsearch data.
• Design and build interactive dashboards in Kibana using various visualization types and techniques.
• Implement best practices for Elasticsearch and Kibana administration, optimization, and troubleshooting.

This instructor-led, live training in Guatemala is aimed at system administrators who wish to set up an ELK stack (Elasticsearch, Logstash, Kibana). Note that a minimum of 3 delegates is needed for this course to run.

The training starts with a discussion of ELK architecture and functionality, then moves on to live lab implementation and practice. Hands-on exercises make up an important part of the training and give participants a chance to put into practice their knowledge while receiving feedback on their progress.

This training introduces Kibana to the users of Elasticsearch.

Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis and visualize your data in a variety of charts, tables, and maps.

Kibana makes it easy to understand large volumes of data. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time.

This instructor-led, live training in Guatemala (online or onsite) is aimed at data scientists who wish to use H2O AutoML to automoate the process of building and selecting the best machine learning algorithm and parameters.

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

• Automate the machine learning workflow.
• Automatically train and tune many machine learning models within a specified time range.
• Train stacked ensembles to arrive at highly predictive ensemble models.

This instructor-led, live training in Guatemala (online or onsite) is aimed at machine learning practitioners who wish to use Auto-sklearn to automate the process of selecting and optimizing a machine learning model.

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

• Automate the process of training highly efficient machine learning models.
• Build highly accurate machine learning models while bypassing the more tedious tasks of selecting, training and testing different models.
• Use the power of machine learning to solve real-world business problems.