Predictive Modelling with R Training Course

This instructor-led, live training in Sweden (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 in Sweden (online or on-site) is designed for business analysts who wish to automate trading using algorithmic strategies, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized increments.
• Lower trade-related costs by leveraging algorithmic trading.
• Automatically track stock prices and execute trades.

In this instructor-led, live training in Sweden, participants will develop the appropriate mindset for engaging with Big Data technologies, evaluate their impact on current 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 outcomes.

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

• Integrate Big Data technology with traditional data gathering processes to construct a comprehensive narrative during investigations.
• Implement industrial-grade big data storage and processing solutions for data analysis.
• Develop a proposal for adopting the most suitable tools and processes to facilitate a data-driven approach to criminal investigation.

Big Data encompasses solutions designed for storing and processing extensive datasets. Originally developed by Google, these Big Data technologies have evolved and inspired numerous other initiatives, many of which are open-source. R is a widely used programming language within the financial sector.

Audience

This course is designed for professionals who aim to make sense of accessible data or analyse unstructured data found online (such as Twitter, LinkedIn, etc.).

It is primarily targeted at decision-makers and individuals responsible for determining which data warrants collection and analysis.

While it is not intended for those configuring the solution, participants will still benefit from understanding the broader context.

Delivery Mode

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

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

Content and Software Used

All software utilised is updated for each course iteration, ensuring the latest versions are employed.

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

This instructor-led live training in Sweden (online or onsite) is designed for data scientists and analysts who want to automate, assess, 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 data.
• Build and train models to identify key variables and achieve prediction goals.
• Interpret models to generate actionable insights that support business decision-making.
• Monitor and manage models to ensure optimal prediction performance.

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

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

• Grasp the core principles of predictive AI and generative models.
• Leverage AI-powered tools for predictive coding, forecasting, and automation.
• Implement Large Language Models (LLMs) and transformers for text and code generation.
• Apply time-series forecasting techniques and AI-driven 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 Sweden (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.

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

Predictive analytics involves leveraging data analytics to forecast future outcomes. This methodology utilizes data combined with data mining, statistical analysis, and machine learning techniques to construct predictive models capable of anticipating future events.

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

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

• Construct predictive models to analyze patterns in historical and transactional data
• Employ predictive modeling to identify potential risks and opportunities
• Develop 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

Format of the course

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

This instructor-led, live training in Sweden (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 Sweden (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.

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

In this instructor-led live training, participants will learn how to utilize 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
• Mashup data and create predictive models
• Operationalize predictive analytics within a business process
• Troubleshoot and optimize RapidMiner

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

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

This instructor-led live training, available online or on-site, is designed for analysts, researchers, and professionals at the beginner to intermediate level 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 able to:

In this instructor-led live session, attendees will discover how to manipulate and visualize data using the tools within the Tidyverse framework.

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

• Individuals new to the R language
• Beginners in data analysis and data visualization

• A blend of lecture, discussion, exercises, and extensive hands-on practice

• Perform data analysis and create visually compelling charts
• Draw meaningful insights from various sample datasets
• Filter, sort, and summarize data to address exploratory questions
• Transform processed data into informative line plots, bar charts, histograms, and more
• Import and filter data from diverse sources, including Excel, CSV, and SPSS files