Predictive Analytics Training in Belgrade

This instructor-led, live training in Belgrade (online or onsite) is designed for 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 Belgrade (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.

Upon completing this training, participants will be able to:

• Grasp 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 Belgrade (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 Belgrade (online or onsite) is designed for 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 anticipate 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 Belgrade, participants will learn the strategic approach to Big Data technologies, assess their impact on existing processes and policies, and implement these technologies to identify criminal activity and prevent crime. We will examine case studies from law enforcement organizations worldwide to gain insights into their adoption strategies, challenges, and results.

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

• Integrate Big Data technologies with traditional data collection methods to reconstruct narratives during investigations.
• Deploy industrial-grade Big Data storage and processing solutions for comprehensive data analysis.
• Develop proposals for adopting the most suitable tools and processes to facilitate a data-driven approach to criminal investigations.

Audience

This course is designed for individuals seeking to interpret accessible data or analyze unstructured information found online, such as data from Twitter and LinkedIn.

It primarily targets decision-makers and professionals responsible for determining which data should be collected and analyzed.

While not tailored for technical configurators, these individuals will still gain valuable high-level insights.

Delivery Mode

Participants will be introduced to working examples, primarily utilizing open-source technologies.

The format combines short lectures with participant-led presentations and practical exercises.

Content and Software Used

The software used is updated with every course iteration to ensure the latest versions are utilized.

The curriculum covers the entire data lifecycle—from acquisition and formatting to processing and analysis—along with techniques for automating decision-making through machine learning.

This instructor-led live training in Belgrade (online or onsite) is designed for data scientists and 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, freely available programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly adopted by managers and data analysts within both corporate environments and academic institutions. R offers a comprehensive array of packages tailored for data mining tasks.

Predictive analytics involves leveraging data analytics to forecast future outcomes. This methodology combines data with techniques from data mining, statistics, and machine learning to construct predictive models capable of anticipating upcoming events.

In this instructor-led live training, participants will learn to utilize Matlab for constructing predictive models and applying them to large-scale datasets to predict future occurrences based on historical data.

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

• Develop predictive models to analyze patterns within historical and transactional data
• Employ predictive modeling to identify potential risks and opportunities
• Construct mathematical models that capture significant trends
• Leverage data from devices and business systems to minimize waste, conserve time, or reduce costs

Audience

• Developers
• Engineers
• Domain experts

Course Format

• A combination of lectures, discussions, exercises, and extensive hands-on practice

R is a free, open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by data analysts and managers across both corporate environments and academic institutions. R offers an extensive range of packages tailored for data mining tasks.

RapidMiner is an open-source data science software platform designed for rapid application prototyping and development. It features an integrated environment supporting data preparation, machine learning, deep learning, text mining, and predictive analytics.

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

Upon completing this training, participants will be able to:

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

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

• A mix of lectures, discussions, exercises, and extensive hands-on practice

Note

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

This instructor-led live training (online or onsite) is designed for beginner to intermediate analysts, researchers, and professionals who want to utilize SPSS for data preparation, statistical analysis, and predictive modeling.