Online Predictive Analytics Training in Slovakia

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level developers who wish to build AI-powered applications using predictive analytics and generative models.

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

• Understand the fundamentals of predictive AI and generative models.
• Utilize AI-powered tools for predictive coding, forecasting, and automation.
• Implement LLMs (Large Language Models) and transformers for text and code generation.
• Apply time-series forecasting and AI-based recommendations.
• Develop and fine-tune AI models for real-world applications.
• Evaluate ethical considerations and best practices in AI deployment.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level data professionals who wish to apply machine learning techniques to data-driven business problems, including sales forecasting and predictive modeling using neural networks.

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

• Understand the core concepts and types of machine learning.
• Apply key algorithms for classification, regression, clustering, and association analysis.
• Perform exploratory data analysis and data preparation using Python.
• Use neural networks for nonlinear modeling tasks.
• Implement predictive analytics for business forecasting, including sales data.
• Evaluate and optimize model performance using visual and statistical techniques.

This instructor-led, live training in Slovakia (online or onsite) is aimed at beginner-level IT professionals who wish to grasp the fundamentals of Predictive AI.

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

• Understand the core concepts of Predictive AI and its applications.
• Collect, clean, and preprocess data for predictive analysis.
• Explore and visualize data to uncover insights.
• Build basic statistical models to make predictions.
• Evaluate the performance of predictive models.
• Apply Predictive AI concepts to real-world scenarios.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level DevOps professionals who wish to integrate predictive AI into their DevOps practices.

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

• Implement predictive analytics models to forecast and solve challenges in the DevOps pipeline.
• Utilize AI-driven tools for enhanced monitoring and operations.
• Apply machine learning techniques to improve software delivery workflows.
• Design AI strategies for proactive issue resolution and optimization.
• Navigate the ethical considerations of using AI in DevOps.

In this instructor-led, live training in Slovakia, participants will learn the mindset with which to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement organizations around the world will be examined to gain insights on their adoption approaches, challenges and results.

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

• Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation.
• Implement industrial big data storage and processing solutions for data analysis.
• Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation.

Audience

If you are looking to make sense of the data at your disposal or want to analyze unstructured data available online (such as on Twitter, LinkedIn, etc.), this course is designed for you.

The primary focus is on decision-makers and individuals who need to determine which data is worth collecting and analyzing.

While it is not intended for those configuring the solution, they will still gain valuable insights into the broader context.

Delivery Mode

Throughout the course, participants will be presented with practical examples of mostly open-source technologies.

Short lectures will be followed by presentations and simple exercises for the attendees to engage in.

Content and Software Used

All software used is updated each time the course is conducted, ensuring that we utilize the latest versions available.

The course covers the entire process from data acquisition, formatting, processing, and analysis, with a focus on how to automate decision-making processes using machine learning.

This instructor-led, live training in Slovakia (online or onsite) is aimed at data scientists and data analysts who wish to automate, evaluate, and manage predictive models using DataRobot's machine learning capabilities.

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

• Load datasets in DataRobot to analyze, assess, and quality check data.
• Build and train models to identify important variables and meet prediction targets.
• Interpret models to create valuable insights that are useful in making business decisions.
• Monitor and manage models to maintain an optimized prediction performance.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly being adopted by managers and data analysts in both corporate and academic settings. R offers a vast array of packages that facilitate data mining tasks.

Predictive analytics involves using data analysis to make forecasts about future events. This approach combines data with techniques such as data mining, statistics, and machine learning to develop models that can predict future outcomes.

In this instructor-led, live training, participants will learn how to use Matlab to create predictive models and apply them to large datasets to forecast future events based on the available data.

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

• Create predictive models to identify patterns in historical and transactional data
• Use predictive modeling to uncover risks and opportunities
• Develop mathematical models that capture significant trends
• Leverage data from devices and business systems to optimize processes, save time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

• Part lecture, part discussion, with exercises and extensive hands-on practice

R is an open-source, freely available programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly being adopted by both corporate professionals and academic researchers. R offers a vast array of packages that facilitate data mining and other advanced analytical tasks.

RapidMiner is an open-source data science software platform designed for swift application prototyping and development. It provides a comprehensive environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.

In this instructor-led, live training, participants will learn how to use RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models.

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

• Install and configure RapidMiner
• Prepare and visualize data using RapidMiner
• Validate machine learning models
• Integrate data and create predictive models
• Incorporate predictive analytics into business processes
• Troubleshoot and optimize RapidMiner

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

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

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level analysts, researchers, and professionals who wish to use SPSS for data preparation, statistical analysis, and predictive modeling.