Predictive Modelling with R Training Course

This instructor-led, live training in Italy (online or onsite) is aimed at intermediate-level advanced R users who wish to use R to build faster workflows, improve code quality, and handle more complex analysis tasks.

By the end of this training, participants will be able to: create reusable functions, improve data workflows, debug and optimize code, and produce reproducible reports.

This instructor-led, live training session Italy (online or onsite) is tailored for business analysts who wish to automate trading processes using algorithmic trading, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized intervals.
• Lower transaction costs associated with trading through the use of algorithmic strategies.
• Automatically track stock prices and execute trades accordingly.

In this instructor-led live training located in Italy, participants will learn how to approach Big Data technologies, assess their impact on existing processes and policies, and implement them to identify criminal activity and prevent crime. Case studies from law enforcement organizations around the world will be analyzed to gain insights into their adoption strategies, 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.

Big Data denotes solutions designed for the storage and processing of extensive data sets. Initially pioneered by Google, these Big Data solutions have evolved and spurred the creation of other similar projects, many of which are accessible as open-source software. R has established itself as a widely adopted programming language within the financial sector.

Target Audience

If you are looking to make sense of the data you have access to, or wish to analyze unstructured data available on the internet (such as Twitter, LinkedIn, etc.), this course is ideal for you.

It is primarily designed for decision-makers and professionals who need to determine which data is valuable to collect and analyze.

While it is not intended for individuals configuring the solution, those involved in setup will still benefit from understanding the broader context.

Delivery Mode

Throughout the course, delegates will be presented with working examples of primarily open-source technologies.

Short lectures will be followed by participant presentations and simple exercises.

Content and Software Used

All software utilized is updated each time the course runs, ensuring we work with the latest available versions.

The curriculum covers the entire process from obtaining, formatting, processing, and analyzing data, to explaining how to automate decision-making processes with machine learning.

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

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

• Load datasets into DataRobot to analyze, assess, and perform quality checks on the data.
• Construct and train models to identify key variables and achieve prediction objectives.
• Interpret models to generate valuable insights that support business decision-making.
• Monitor and manage models to ensure optimal prediction performance.

This instructor-led live training in Italy (online or onsite) is designed for intermediate developers seeking to build AI-powered applications using predictive analytics and generative models.

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

• Grasp the core principles of predictive AI and generative models.
• Leverage AI-driven tools for predictive coding, forecasting, and automation.
• Deploy Large Language Models (LLMs) and transformers for generating text and code.
• Apply time-series forecasting and AI-based recommendation systems.
• Develop and fine-tune AI models for practical, real-world use cases.
• Assess ethical implications and adhere to best practices in AI deployment.

This instructor-led, live training in Italy (available online or onsite) is designed for beginner-level IT professionals who want to grasp the fundamentals of Predictive AI.

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

• Comprehend the core concepts of Predictive AI and its practical applications.
• Gather, clean, and preprocess data for predictive analysis.
• Explore and visualize data to uncover key insights.
• Construct basic statistical models to generate predictions.
• Assess the performance of predictive models.
• Apply Predictive AI concepts to real-world scenarios.

R is an open-source programming language dedicated to statistical computing, data analysis, and graphical visualization. It is increasingly adopted by managers and data analysts within both corporate environments and academic institutions. R offers a vast array of packages tailored for data mining and advanced analytics.

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

During this instructor-led live training, participants will learn how to utilize Matlab to develop predictive models and apply them to large datasets for forecasting future trends based on historical information.

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

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

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

This instructor-led, live training in Italy (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:

• Grasp the fundamental concepts and categories of machine learning.
• Apply essential algorithms for classification, regression, clustering, and association analysis.
• Conduct exploratory data analysis and prepare data using Python.
• Utilize 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 Italy (online or onsite) targets intermediate-level DevOps professionals who aim to integrate predictive AI into their operational workflows.

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

• Deploy predictive analytics models to anticipate and address challenges within the DevOps pipeline.
• Employ AI-driven tools to improve monitoring and operational efficiency.
• Apply machine learning techniques to optimize software delivery workflows.
• Develop AI strategies aimed at proactive issue resolution and process optimization.
• Understand and navigate the ethical implications of implementing AI in DevOps.

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

During this instructor-led live training, participants will learn how 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
• Mash up data and create predictive models
• Operationalize predictive analytics within a business process
• Troubleshoot and optimize RapidMiner

Audience

• Data scientists
• Engineers
• Developers

Course Format

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

Note

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

This instructor-led, live training session (available online or on-site) targets analysts, researchers, and professionals at the beginner to intermediate levels who aim to leverage SPSS for data preparation, statistical analysis, and predictive modeling.

Target Audience

Course Format

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

This instructor-led, live training enables participants to master data manipulation and visualization techniques using the tools provided by Tidyverse.

Tidyverse comprises a suite of versatile R packages designed for cleaning, processing, modeling, and visualizing data. Key packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Individuals new to the R programming language
• Individuals new to data analysis and data visualization

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

• Conduct data analysis and generate compelling visualizations
• Derive meaningful insights from various sample datasets
• Filter, sort, and summarize data to address exploratory questions
• Convert processed data into informative charts, such as line plots, bar plots, and histograms
• Import and filter data from diverse sources, including Excel, CSV, and SPSS files