Educational Resources
This page is a collection of books and references that have shaped my expertise in data analytics, economics, predictive modeling, and technology. Organized by topic, it includes what I’ve found most valuable and what I’m currently exploring.
Whether you’re into analytics, programming, or predictive modeling, I hope these resources help you as much as they’ve helped me. Got a recommendation? Let’s connect!
Data Analytics & Visualization
- R for Data Science – A comprehensive introduction to data science using R, covering data wrangling, visualization, and modeling.
- ggplot2: Elegant Graphics for Data Analysis – A detailed guide to the ggplot2 package, one of the most powerful tools for data visualization in R.
- Mastering Microsoft Power BI – Covers advanced visualization techniques, data modeling, and dashboarding in Power BI.
Programming & Development
- Advanced R – Explores the deeper workings of R, including functional programming, metaprogramming, and performance optimization.
- Numerical Methods for Data Science – A mathematical foundation for numerical methods used in machine learning and data science.
- Design and Analysis of Experiments – Focuses on experimental design principles and statistical analysis techniques using R.
Economics & Predictive Modeling
- An Introduction to Statistical Learning with Applications in R – A beginner-friendly guide to statistical learning, regression, classification, and machine learning techniques.
- Mining of Massive Datasets – Covers large-scale data mining techniques, including clustering, recommendation systems, and web search.
- Time Series Analysis and Its Applications with Examples in R – Provides a practical guide to time series modeling and forecasting, with real-world applications in R.
Business Intelligence & Decision Science
- LearnDataSci – A resource hub covering Python, SQL, machine learning, and practical applications for business intelligence.
- The Definitive Guide to Power Query – Covers Power Query’s capabilities for transforming and shaping data in Excel and Power BI.
- The Definitive Guide to DAX – Explores DAX, the core data modeling language for Power BI and Analysis Services.
- The BABOK – The Business Analysis Body of Knowledge (BABOK) is a key resource for business analysis best practices and frameworks.
Data Infrastructure
- Engineering Production-Grade Shiny Apps – A guide to building robust, maintainable Shiny applications for data-driven web applications.
- Mastering Shiny – Explores how to build interactive web applications using Shiny in R.
- Shiny in Production – Focuses on deploying and scaling Shiny applications effectively.
- Reproducible Research in R – Covers tools and workflows for reproducible and transparent research.
- R Markdown Cookbook – A practical guide to using R Markdown for dynamic documents, reports, and presentations.
- The Data Warehouse Toolkit – A foundational guide on designing scalable and efficient data warehouses.