Training Overview

Win-Vector LLC offers customized instructor led corporate training on topics of statistics, data science, and using the R analysis platform.

Our training is tuned to the needs of your team. Content is based on current literature, best practices, consulting experience, our book Practical Data Science with R, and our popular video series Introduction to Data Science.

Training is assembled from modules. Clients may choose from many topics including:

  • Data Science Project Planning:

    Setting expectations, agile data science methodology, scoping projects, and tracking value of results.

  • Beginning R programming for analysts:

    Teaches analysts how to move their work from spreadsheets and GUIs to reusable and reproducible procedures using R, knitr, and shiny.

  • Basic data science practices:

    Teaches analytically minded audiences the basics of the actual practice of data science: finding ROI in business questions, working with data, and critical tests and reports.

  • Shiny development:

    Teaches how to share your data science projects and results as interactive Shiny applications.

  • Advanced R programming:

    Teaches the fundamentals of writing efficient high-performance R code, including working with large data and parallelism.

  • Advanced data transforms:

    Teaches how to reshape data for analysis. Learn how to convert log data into data ready for analysis. Learn how to aggregate and pivot data using SQL, dplyr, and other tools.

  • Defensive coding and analysis techniques:

    Learn how to write reliable code and design reliable analyses.

  • Statistics for data scientists:

    A re-teaching of advanced statistics adapted to be used in conjunction with modern black-box machine learning techniques.

  • Machine learning for statisticians:

    A re-teaching of state of the art machine learning techniques, grounded in standard statistical terminology.

  • Statistical transformations for analysis:

    How to re-process data for better results. Learn how to use (and alter) distributional facts about your data to get better results from your models.

  • Domain specific deep-dives:

    Some examples: A/B testing, design and management of experiments, interpretation of results.

We then scope the course and deliver on-site custom training, including programming and analysis exercises with real-world data sets. When possible, we can adapt your data to our exercises.

For quotes, reference customers, or discussion please reach out to us at .

We also offer data science consulting and contracting.