Introductory R (Basic to Intermediate) Training Course

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

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

• Utilize algorithms to rapidly buy and sell securities at specialized increments.
• Lower costs associated with trading through the application of algorithmic methods.
• Automatically monitor stock prices and execute trades.

Big Data refers to solutions designed for the storage and processing of massive datasets. Originally developed by Google, these Big Data solutions have evolved and inspired other similar projects, many of which are now available as open-source software. R is a widely adopted programming language within the financial industry.

This instructor-led live training Argentina (online or onsite) is designed for data analysts who want to use R within SAS for cluster analysis.

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

• Use cluster analysis for data mining.
• Master R syntax for clustering solutions.
• Implement hierarchical and non-hierarchical clustering.
• Make data-driven decisions to help to improve business operations.

In today's business landscape, data analytics serves as an essential instrument. This course emphasizes cultivating practical, hands-on skills in data analysis. Our primary goal is to empower participants to provide evidence-based responses to key questions:  

What has happened?

• processing and analyzing data
• producing informative data visualizations

What will happen?

• forecasting future performance
• evaluating forecasts

What should happen?

• turning data into evidence-based business decisions
• optimizing processes

This instructor-led, live training in Argentina (online or onsite) is aimed at beginner-level professionals who wish to clean and analyze data, make statistical projections, and create insightful visualizations using these tools.

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

• Understand the basics of Python, R, Power Query, and Power BI for data analysis.
• Clean and organize datasets using Python and Power Query.
• Perform statistical analysis and projections with R.
• Create professional dashboards and reports with Power BI.
• Integrate and analyze data from multiple sources effectively.

R is a widely-used, open-source environment designed for statistical computing, data analytics, and graphical representation. This course provides students with an introduction to the R programming language, covering fundamental concepts, key libraries, and advanced topics. Participants will learn to perform advanced data analytics and create visualizations using real-world datasets.

Target Audience

Developers and data analysts

Duration

3 days

Format

Lectures and Hands-on

This instructor-led, live training in Argentina (online or onsite) is aimed at beginner-level professionals who wish to gain a mastery of the fundamentals of R and how to work with data.

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

• Understand the R programming environment and RStudio interface.
• Import, manipulate, and explore datasets using R commands and packages.
• Perform basic statistical analysis and data summarization.
• Generate visualizations using both base R and ggplot2.
• Manage workspaces, scripts, and packages effectively.

This instructor-led, live training Argentina (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

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

• Understand the fundamentals of forecasting techniques in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Utilize the 'forecast' package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

This instructor-led live training in Argentina (online or onsite) is tailored for data scientists interested in programming with Python and R for KNIME.

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

• Plan, build, and deploy machine learning models in KNIME.
• Make data driven decisions for operations.
• Implement end to end data science projects.

It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.

This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.

By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.

Format of the Course

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

In this instructor-led, live training, participants will learn advanced techniques for Machine Learning with R as they step through the creation of a real-world application.

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

• Understand and implement unsupervised learning techniques
• Apply clustering and classification to make predictions based on real world data.
• Visualize data to quickly gain insights, make decisions and further refine analysis.
• Improve the performance of a machine learning model using hyper-parameter tuning.
• Put a model into production for use in a larger application.
• Apply advanced machine learning techniques to answer questions involving social network data, big data, and more.

Target Audience

• Managers
• Developers
• Scientists
• Students

Course Format

Online instruction with discussion OR in-person workshops

R is a widely used programming language in the financial sector, supporting applications that range from core trading platforms to sophisticated risk management systems.

In this instructor-led live training, participants will learn how to leverage R to build practical solutions for a variety of finance-specific challenges.

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

• Grasp the core fundamentals of the R programming language
• Select and apply R packages and techniques to organize, visualize, and analyze financial data from diverse sources (such as CSV, Excel, databases, and web APIs)
• Develop applications that address issues like asset allocation, risk analysis, and investment performance
• Troubleshoot, integrate, deploy, and optimize R applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training focuses on providing solutions for key challenges faced by finance professionals. If you have a specific topic, tool, or technique you would like to add or explore in greater detail, please contact us to arrange a customized session.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphics. It is increasingly utilized by managers and data analysts within both corporate and academic sectors. R has also gained popularity among statisticians, engineers, and scientists who may lack extensive computer programming skills, as it offers an accessible interface. Its widespread adoption stems from the growing demand for data mining applications, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R provides a comprehensive array of packages tailored for data mining tasks.

This course delves into the manipulation of R objects, covering essential skills such as data ingestion, package management, function creation, and the production of insightful visualizations. It also encompasses data analysis through the application of common statistical models. Participants will learn to utilize R software (https://www.r-project.org) via both command-line interfaces and graphical user interfaces (GUI).