Service Description

As a full-time R programmer with specialization in machine learning, statistics, and biomedical data, I mentor students and professionals in developing robust, reproducible, and insightful data workflows. From foundations to publication-ready code, I provide structured, project-based instruction across domains. Beginner to Intermediate Topics: - R Fundamentals: objects, control flow, vectorization - Data Wrangling: dplyr, tidyr, data.table for efficient manipulation - Data Visualization: ggplot2, patchwork, plotly, custom themes - Reporting: RMarkdown, parameterized reports, dashboards Advanced Topics: - Statistical Modeling: GLMs, LMMs, GAMs, survival models (survival, aorsf) - Machine Learning: classification, regression, model tuning (caret, mlr3, xgboost, keras) - Deep Learning: CNNs, VAEs, autoencoders, custom Keras models in R - Bioinformatics: gene filtering, clustering, dimensionality reduction, DE analysis - Spatial & Time-Series Analysis: sf, sp, temporal modeling, autoregressive models - Pipeline Automation & Project Structuring: workflow management, custom packages - App Development: interactive Shiny dashboards, form submission, reactive modeling Whether you’re building a data science capstone, debugging your thesis code, or learning R for professional development, I offer customized sessions with real-world applicability and reproducibility in mind.