Shiny, R and HTML: Merging Data Science and Web Development Training Course

This instructor-led, live training in Greece (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 Greece (available online or onsite) is tailored for business analysts seeking 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 specific, specialized increments.
• Lower costs associated with trading through the application of algorithmic methods.
• Automatically monitor stock prices and execute trades.

Big Data encompasses solutions designed for the storage and processing of large-scale datasets. Initially developed by Google, these Big Data frameworks have evolved and inspired numerous analogous projects, many of which are available as open-source software. R has established itself as a widely used programming language within the financial sector.

This instructor-led, live training in Greece (online or onsite) targets beginner-level data analysts seeking to use R programming for data manipulation, basic analysis, and creating insightful visualizations.

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 Greece (online or onsite) targets data analysts interested in programming with 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.

Data analytics is an essential instrument for modern business. Throughout this course, we will concentrate on cultivating practical, hands-on data analysis skills. Our objective is to empower participants to provide evidence-based answers 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 Greece (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 graphics. This course provides students with an introduction to the R programming language, covering fundamental syntax, essential libraries, and advanced concepts. Participants will engage in advanced data analytics and visualization techniques using real-world datasets.

Target Audience

Developers and Data Analysts

Duration

3 days

Format

Instructional lectures combined with practical, hands-on exercises

This instructor-led, live training in Greece (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 Greece (online or on-site) is aimed at data scientists who wish to program in Python and R for 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.

Unstructured data is estimated to represent over 90% of all existing data, with a significant portion appearing as text. Sources such as blog posts, tweets, social media platforms, and other digital publications continuously contribute to this expanding volume of information.

This instructor-led, live training focuses on extracting valuable insights and meaning from such data. By leveraging the R programming language alongside Natural Language Processing (NLP) libraries, the course integrates concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically decipher the meaning behind textual data. Data samples can be provided in various languages depending on customer requirements.

Upon completion of this training, participants will be capable of preparing datasets (both large and small) from diverse sources and applying appropriate algorithms to analyze and report on their significance.

Format of the Course

• A blend of lectures and discussions, emphasizing extensive hands-on practice, with occasional assessments to gauge understanding.

During this instructor-led, live training, participants will explore advanced Machine Learning techniques in R by building a practical, real-world application step-by-step.

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

• Understand and implement unsupervised learning techniques
• Utilize clustering and classification methods to make predictions based on real-world data.
• Visualize data to quickly gain insights, make informed decisions, and refine analytical approaches.
• Enhance the performance of machine learning models through hyper-parameter tuning.
• Deploy models into production for integration into larger applications.
• Apply advanced machine learning techniques to address challenges involving social network data, big data, and other domains.

R is a widely adopted programming language within the financial sector. It supports financial applications spanning from core trading platforms to comprehensive risk management systems.

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

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

• Grasp the fundamental concepts of the R programming language
• Select and employ R packages and techniques to organize, visualize, and analyze financial data obtained from diverse sources (such as CSV, Excel, databases, web APIs, etc.)
• Construct applications that resolve issues related to asset allocation, risk analysis, investment performance evaluation, 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 for key problems encountered by finance professionals. If there is a specific topic, tool, or technique you wish to explore in greater depth or add to the curriculum, please contact us to arrange for customization.

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 environments and academia. R has also gained popularity among statisticians, engineers, and scientists who may lack extensive programming experience but find its usability appealing. The language's widespread adoption stems from the growing reliance on data mining for objectives such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R offers a comprehensive array of packages tailored for data mining tasks.

R Markdown is an authoring framework that combines executable R code with narrative text to create dynamic and reproducible documents.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level R users who wish to generate automated, dynamic reports using R Markdown for internal documentation, research publications, or web publishing.

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

• Create R Markdown documents with embedded R code chunks and formatted text.
• Generate outputs in multiple formats including HTML, PDF, and Word.
• Use parameterized reports and conditional logic to generate dynamic content.
• Customize document appearance with themes, templates, and LaTeX for professional presentation.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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