Qlik Sense for Data Science Training Course

This instructor-led, live training in Uzbekistan (online or onsite) is tailored for advanced-level DevOps and SRE professionals looking to enhance their alerting and automation skills with Grafana and Prometheus.

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

• Develop and manage advanced alerting rules in Prometheus.
• Connect Prometheus Alertmanager with external tools using webhooks.
• Automate alert responses to resolve issues more quickly.
• Utilize Grafana to visualize and manage alerts efficiently.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at data scientists who wish to use the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a single platform.

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

• Install and configure Anaconda components and libraries.
• Understand the core concepts, features, and benefits of Anaconda.
• Manage packages, environments, and channels using Anaconda Navigator.
• Use Conda, R, and Python packages for data science and machine learning.
• Get to know some practical use cases and techniques for managing multiple data environments.

This instructor-led, live training in Uzbekistan (online or onsite) is designed for intermediate-level DevOps and SRE professionals who aim to create impactful dashboards and optimize their monitoring practices using Grafana and Prometheus.

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

• Master best practices for designing effective dashboards.
• Develop and configure advanced Grafana dashboard components.
• Utilize Grafana templating to create dynamic and reusable dashboards.
• Implement alerting systems to boost operational awareness.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to instrument their applications to export and monitor custom metrics effectively using Prometheus and Grafana.

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

• Understand the importance of custom metrics for application monitoring.
• Instrument applications to export custom metrics for Prometheus.
• Create and configure dashboards in Grafana to visualize custom metrics.
• Apply best practices for integrating monitoring into the development lifecycle.

This instructor-led, live training in Uzbekistan (onsite or remote) is designed for data analysts who wish to use Grafana for monitoring and visualising data.

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

• Set up the necessary development environment to begin creating visualisations in Grafana.
• Configure Grafana for high availability.
• Customise panels and dashboards with data.
• Configure a reverse proxy to ensure fast loading speeds.

This instructor-led, live training in Uzbekistan (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 Uzbekistan (online or onsite) is aimed at intermediate-level system administrators and monitoring professionals who wish to effectively use Grafana for setting up monitoring solutions, managing dashboards, and creating alerts.

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

• Understand the difference between observability and monitoring.
• Install and set up the Grafana server.
• Configure and connect various data sources such as Prometheus, InfluxDB, and ElasticSearch.
• Create, manage, and customize dashboards and charts.
• Use variables and queries to create dynamic dashboards.
• Set up notifications and alerts through Grafana.
• Install and manage plugins to extend Grafana’s functionality.

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

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

• Create and customize Grafana dashboards with various 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 Uzbekistan (online or onsite) targets web developers and DevOps engineers who wish to visualize and monitor data using 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 Uzbekistan (online or onsite) is designed for intermediate-level Grafana users who want to build interactive dashboards featuring drill-down capabilities, dynamic thresholds, and contextual updates.

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

• Create dashboards that respond to user interactions, such as clicking a graph bar
• Implement visual drill-downs that update in-place (without new tabs)
• Configure pie charts and detailed panels based on selection filters
• Use dynamic thresholds that react to user input and real-time data

This instructor-led, live training in Uzbekistan (online or onsite) is designed for beginner-level IT professionals and DevOps practitioners aiming to learn the fundamentals of Grafana and Prometheus.

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

• Understand the purpose and key features of Grafana and Prometheus.
• Install and configure Grafana and Prometheus in a Linux environment.
• Set up basic data sources and dashboards in Grafana.
• Monitor system metrics and visualize data using Prometheus.

This instructor-led, live training in Uzbekistan (online or onsite) is designed for intermediate-level cloud and DevOps engineers aiming to enhance cloud observability using Grafana and Prometheus.

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

• Understand the advantages of integrating Grafana and Prometheus with cloud platforms.
• Set up Prometheus to monitor cloud-based resources.
• Configure Grafana for visualizing cloud service metrics.
• Utilize cloud-native tools and integrations for scalable monitoring.

This instructor-led, live training in Uzbekistan (available online or on-site) is tailored for data scientists and developers who aim to learn and advance their careers in Data Science using Kaggle.

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

• Gain a solid understanding of data science and machine learning.
• Explore key concepts in data analytics.
• Learn about Kaggle and how it operates.

This instructor-led, live training in Uzbekistan (available online or on-site) is tailored for data scientists and developers who wish to utilize Modin to build and implement parallel computations with Pandas, thereby achieving faster data analysis.

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

• Set up the necessary environment to begin developing scalable Pandas workflows with Modin.
• Understand the features, architecture, and advantages of Modin.
• Distinguish between Modin, Dask, and Ray.
• Execute Pandas operations more rapidly using Modin.
• Implement the full Pandas API and its functions.

This instructor-led, live training in Uzbekistan (available online or on-site) is intended for data scientists and developers who wish to leverage RAPIDS to build GPU-accelerated data pipelines, workflows, and visualisations, applying machine learning algorithms such as XGBoost, cuML, and others.

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

• Set up the required development environment to build data models using NVIDIA RAPIDS.
• Understand the key features, components, and advantages of the RAPIDS framework.
• Harness the power of GPUs to accelerate end-to-end data and analytics pipelines.
• Implement GPU-accelerated data preparation and ETL processes using cuDF and Apache Arrow.
• Learn how to carry out machine learning tasks using XGBoost and cuML algorithms.
• Create data visualisations and perform graph analysis using cuXfilter and cuGraph.