Predictive Modelling with R Training Course

This instructor-led live training in Turkey (online or onsite) is designed for intermediate-level R users who aim 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, enhance data workflows, debug and optimize code, and produce reproducible reports.

This instructor-led, live training in Turkey (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

In this instructor-led live training located in Turkey, participants will cultivate the mindset required to approach Big Data technologies, assess their impact on existing workflows and policies, and implement these technologies to identify criminal activity and prevent crime. Case studies from law enforcement organizations worldwide will be reviewed to provide insights into adoption approaches, challenges, and results.

By the conclusion of this training, participants will be capable of:

• Merging Big Data technology with traditional data gathering processes to piece together investigative narratives.
• Implementing industrial big data storage and processing solutions for data analysis.
• Preparing proposals for adopting the most suitable tools and processes to enable a data-driven approach to criminal investigation.

Big Data encompasses solutions designed for the storage and processing of massive datasets. Originally developed by Google, these Big Data frameworks have evolved and inspired numerous similar initiatives, many of which are available as open-source software. R is widely recognized as a leading programming language within the financial sector.

Audience

This course is ideal for professionals seeking to derive meaning from accessible data or to analyze unstructured information found online (such as content from Twitter, LinkedIn, and similar platforms).

The program primarily targets decision-makers and analysts who must determine which data sets are valuable for collection and analysis.

While the course does not focus on technical configuration, those involved in setting up solutions will still gain a valuable high-level perspective.

Delivery Mode

Participants will explore working examples of predominantly open-source technologies throughout the training.

Instruction consists of brief lectures, followed by participant-led presentations and practical exercises.

Content and Software used

All software tools are updated with each course iteration to ensure access to the latest versions available.

The curriculum covers the entire data lifecycle—from acquisition and formatting to processing and analysis—culminating in an explanation of how to automate decision-making through machine learning.

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

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

• Import datasets into DataRobot to analyze, assess, and verify data quality.
• Construct and train models to identify key variables and achieve prediction goals.
• Interpret models to derive valuable insights that support business decision-making.
• Monitor and manage models to ensure optimal prediction performance.

This instructor-led live training in Turkey (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 Turkey (online or onsite) targets beginner-level IT professionals seeking to understand the basics of Predictive AI.

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

• Comprehend the essential concepts of Predictive AI and its applications.
• Collect, clean, and preprocess data for predictive analysis.
• Explore and visualize data to uncover valuable 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 freely available, open-source programming language designed for statistical computing, data analysis, and data visualization. Its popularity is rapidly growing among corporate managers and data analysts across both industry and academia. R boasts a comprehensive ecosystem of packages specifically tailored for data mining.

Predictive analytics involves leveraging data analytics to forecast future outcomes. By combining data with techniques from data mining, statistics, and machine learning, this process establishes predictive models capable of anticipating upcoming events.

Through this instructor-led live training, attendees will learn to utilize Matlab for constructing predictive models and applying them to extensive datasets to predict future trends based on historical information.

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

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

Audience

• Developers
• Engineers
• Domain experts

Course Format

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

This instructor-led, live training in Turkey (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 Turkey (offered online or onsite) targets intermediate-level DevOps professionals who wish to integrate predictive AI into their DevOps workflows.

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

• Deploy predictive analytics models to anticipate and resolve challenges within the DevOps pipeline.
• Employ AI-powered tools to enhance monitoring and operational capabilities.
• Apply machine learning techniques to optimize software delivery workflows.
• Develop AI strategies for proactive problem resolution and process optimization.
• Understand and address the ethical implications 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 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 with 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

• Part lecture, part discussion, exercises and heavy 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.

Audience

Course Format

Upon completing this training, participants will be able to:

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

The Tidyverse comprises a suite of powerful 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 programming language
• Beginners in data analysis and data visualization

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

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