Learn R Programming - ML
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Learn R Programming: Data Science, Statistics & Machine Learning — All in One App. Master the language that powers the world's top data scientists, biostatisticians, and quantitative analysts. Whether you're a complete beginner or advancing your career, Learn R takes you from your first line of code to building production-ready machine learning models — entirely on your iPhone or iPad.
Why Learn R?
R is the gold standard for statistical computing, data analysis, and academic research. Used by Harvard, MIT, Pfizer, and the FDA, R opens doors to careers in data science, bioinformatics, finance, geospatial analysis, and AI.
Core R Programming:
- R syntax, data types, vectors, matrices, data frames, and lists
- Control flow, loops, functions, and object-oriented programming
- Functional programming with purrr and the apply family
- Performance optimization, profiling, and Rcpp integration
- Secure coding best practices and memory management
Tidyverse & Data Wrangling:
- dplyr for lightning-fast data manipulation
- ggplot2 for publication-quality visualizations
- tidyr, readr, stringr, forcats, and tibble
- Modern data pipelines with the pipe operator
Data Science & Statistics:
- Descriptive and inferential statistics
- Hypothesis testing, regression, ANOVA, and probability
- End-to-end data science workflows
- Exploratory data analysis and data cleaning
Machine Learning & AI:
-caret, tidymodels, random forests, SVMs, and clustering
- Deep learning with Keras, TensorFlow, and Torch for R
- Natural language processing (NLP) and text mining
- Time series forecasting with ARIMA and Prophet
- Reinforcement learning fundamentals
- Big data with data.table and sparklyr
Web, APIs & Deployment:
- Build interactive dashboards with Shiny and shinydashboard
- Create REST APIs with Plumber
- Web scraping with rvest and httr
- Quarto for reports, presentations, and books
- Database integration (MySQL, PostgreSQL, MongoDB, SQLite)
Domain-Specific Tracks:
- Bioinformatics: Bioconductor, genomic data, sequence analysis
- Finance: Quantitative analysis, portfolio modeling, risk management
- GIS & Spatial: sf, raster, leaflet, and geospatial mapping
Career & Ecosystem:
- Career paths: data scientist, biostatistician, quant analyst, researcher
- Package development and publishing to CRAN
- Reproducible research with renv and containers
- Git & GitHub for version control
- Complementary skills: Python, SQL, Julia, Docker
Run Real R Code Anywhere:
Our built-in code compiler lets you write and execute R code instantly. Test dplyr pipelines, plot with ggplot2, build regression models, and debug functions — no laptop required.
AI-Powered Learning :
- Smart Flashcards:AI generates Q&A flashcards from any lesson
- Quiz Hints: Progressive Socratic hints when you're stuck
- Daily AI Tips: Personalized coding tips every morning
- Note Intelligence: Summarize and simplify your notes instantly
Quick-Reference Cheat Sheets:
10+ searchable cheat sheets covering R basics, data structures, dplyr, ggplot2, statistics, machine learning, and best practices — always one tap away.
Structured for Retention:
- Bite-sized lessons designed for mobile
- Daily streaks and progress tracking
- Bookmark lessons and create personal notes
- Offline access to all content
Learn R Programming today to start your R coding journey: master R data analysis, ggplot2, dplyr, and every R skill you need!
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- Shahbaz Khan
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- 168.3 MB
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- iPhone
iOS 17 이상 필요 - iPad
iPadOS 17 이상 필요 - Mac
macOS 14.0 이상 및 Apple M1 칩 이상이 탑재된 Mac이 필요 - Apple Vision
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