Shiny App Web Development with R Training Course

This instructor-led, live training in Romania (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 Romania (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:

• Use algorithms to rapidly buy and sell securities at specialized intervals.
• Reduce costs associated with trading through algorithmic trading.
• Automatically monitor stock prices and execute trades.

Big Data refers to solutions designed for storing and processing large datasets. Initially developed by Google, these Big Data solutions have evolved and inspired similar projects, many of which are open-source. R is a popular programming language in the financial industry.

This instructor-led live training in Romania (online or onsite) is designed for beginner-level data analysts who wish to use R programming to manipulate data, perform basic analysis, and create compelling visualizations for insights.

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

• Understand the basics of R Programming.
• Apply fundamental data science processes.
• Create visual representations of data.

This instructor-led live training in Romania (online or onsite) is aimed at data analysts who wish to program with R in 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.

Data analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to 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 Romania (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 utilized, open-source environment designed for statistical computing, data analytics, and data visualization. This course provides an introduction to the R programming language for students, covering foundational language concepts, essential libraries, and advanced techniques, including the application of sophisticated data analytics and graphing methods on real-world datasets.

Audience

Developers / data analysts

Duration

3 days

Format

Lectures and Hands-on

This instructor-led live training in Romania (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 Romania (online or onsite) is designed for data scientists looking to program with Python and R in KNIME.

By the end 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.

R is a widely used programming language within the financial sector. Its applications range from core trading systems to sophisticated risk management tools.

Through this instructor-led live training, participants will acquire the skills to utilize R for creating practical applications that address specific financial challenges.

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

• Grasp the core principles of the R programming language
• Choose and apply R packages and methodologies to organize, visualize, and analyze financial data sourced from various platforms (such as CSV, Excel, databases, and web APIs)
• Develop applications capable of solving issues related to asset allocation, risk analysis, investment performance, and other areas
• Troubleshoot, integrate, deploy, and optimize R applications

Audience

• Developers
• Analysts
• Quantitative Analysts

Course Format

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

Note

• This training is designed to offer solutions to key problems encountered by finance professionals. Should you wish to explore a specific topic, tool, or technique in greater detail, please contact us to make arrangements.

R is an open-source, free 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. Additionally, R has gained a following among statisticians, engineers, and scientists who may lack traditional programming expertise but appreciate its user-friendly nature. The language's popularity stems from the growing reliance on data mining for diverse objectives, such as optimizing pricing strategies, accelerating pharmaceutical discovery, and refining financial models. R offers a comprehensive suite of packages tailored for data mining tasks.

This course provides a deep dive into object manipulation in R, covering essential skills such as data ingestion, package management, function creation, and the generation of insightful visualizations. Participants will also learn to analyze data using standard statistical models. The curriculum demonstrates how to utilize the R software (https://www.r-project.org) effectively, both through command-line interfaces and graphical user interfaces (GUIs).

R is a free, open-source programming language designed for statistical computing, data analysis, and graphical visualization. Its user base is expanding among corporate managers, data analysts, academic researchers, as well as statisticians, engineers, and scientists who may lack advanced programming expertise, thanks to its user-friendly nature. The tool's widespread adoption stems from the growing demand for data mining across various sectors, including setting competitive prices, accelerating drug discovery, and optimizing financial models. R offers a comprehensive ecosystem of packages tailored for data mining and analysis.