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

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

Big Data encompasses solutions designed to store and process vast amounts of information. Initially developed by Google, these Big Data solutions have evolved and inspired numerous similar projects, many of which are now available as open-source. R has established itself as a widely used programming language within the financial sector.

This instructor-led, live training in Mexico (online or onsite) is aimed at beginner-level data analysts who wish to use R programming to manipulate data, perform basic data 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, offered online or on-site, is targeted at data analysts who want 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.

In today's business landscape, data analytics is an essential instrument. Throughout this course, we will concentrate on building practical skills for hands-on data analysis. The primary 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 Mexico (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 platform for statistical computing, data analytics, and graphics. This course provides students with an introduction to the R programming language, covering language fundamentals, libraries, and advanced topics. Participants will learn advanced data analytics and visualization techniques using real-world datasets.

Target Audience

Developers and data analytics professionals

Duration

3 days

Format

Lectures and Hands-on Exercises

This instructor-led, live training in Mexico (online or onsite) is designed for intermediate-level data analysts and business professionals who wish to conduct 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 Mexico (online or onsite) 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.

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 master advanced machine learning techniques using R by working through the development of a real-world application.

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

• Understand and implement unsupervised learning techniques
• Apply clustering and classification methods to make predictions based on real-world data.
• Visualize data to quickly gain insights, make informed decisions, and further refine analysis.
• Improve the performance of a machine learning model using hyperparameter tuning.
• Deploy a model into production for integration into a larger application.
• Apply advanced machine learning techniques to address inquiries involving social network data, big data, and more.

R is a widely used programming language in the financial sector. Its applications span from core trading systems to risk management platforms.

In this instructor-led live training, participants will learn how to leverage R to build practical applications that address specific financial challenges.

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

• Grasp the fundamentals of the R programming language
• Select and use R packages and techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web, etc.)
• Develop applications to solve problems related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize R applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training is designed to provide solutions for key challenges faced by finance professionals. If you have a specific topic, tool, or technique you wish to include or expand upon, please contact us to make arrangements.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphics. It is increasingly adopted by managers and data analysts in both corporate and academic settings. R is also favored by statisticians, engineers, and scientists who may lack advanced programming skills, due to its user-friendly nature. Its rising popularity stems from the growing reliance on data mining for objectives such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R supports a vast 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.