A hands-on learning platform for analytics, statistics, cloud computing and data science. Learn R,Python, SQL, and the core mathematical ideas behind modern AI using real tools, not simulations. Launch cloud-based RStudio or JuypyterHub directly in your browser, complete guided modules, build projects, and develop skills designed for real-world workflows. No setup. No installs. Just learn.
Learn by doing, not watchingA learning environment designed for modern analytics, cloud-native workflows, and real-world problem solving.
Use RStudio without installing anything. Just log in, explore datasets, write code, and build models directly from your browser.
Beginner to advanced lessons that teach the foundations of statistics, data wrangling, visualization, modelling, and more.
Every lesson comes with hands-on code examples, exercises, and projects inside RStudio or connected tools for maximum retention.
Start in R, add SQL, and grow into cloud, infrastructure, and AI fundamentals with short, focused courses that mirror real work.
Learn the R language from scratch — objects, scripts, and the core skills to read, transform, and summarise real datasets.
Move from “I can run R” to “I can analyse data” using tidyverse tools for wrangling, joins, and visualisation.
Learn how to query databases with SQL — selecting, filtering, grouping and joining tables to answer business questions.
Build the core linear algebra, calculus, and probability intuition that powers modern machine learning and AI.
Get comfortable with the R interface, syntax, and key data structures by building scripts directly in RStudio.
Learn data wrangling, joins, and visualisation using the tidyverse, with practical examples drawn from real datasets.
Apply statistical methods to real problems: sampling, tests, and simple models, all coded step-by-step in R.
Write your first SELECT queries and learn the foundations of working with relational data for analysis.
Combine tables, group results, and calculate metrics — the core patterns behind dashboards and reporting.
Learn the patterns that power real-world dashboards: window functions, dates, and queries designed for BI tools.
Learn the core AWS services used in analytics: S3, EC2, RDS, IAM basics, and how they plug into R and SQL workflows.
Get comfortable with SSH, the terminal, file systems, users, and services — the essentials for working on VPS and cloud machines.
Learn how to host RStudio Server and a database on your own VPS: networking basics, HTTPS, and keeping your stack maintainable.
Build the mathematical foundations behind AI: linear algebra for vectors and matrices, calculus for optimisation, and probability for uncertainty.
Understand how neural networks actually work: layers, activation functions, backpropagation, and how these ideas show up in modern deep learning.
A curated sequence that takes you from zero to running analyses: core R, tidyverse, SQL for analytics, and a capstone project using both.
Focus on the skills used in reporting roles: automating reports, building reproducible analysis scripts, and combining R with SQL exports.
Quantyl will expand into Python, Streamlit, and machine learning environments — all browser-based, all practical, no installation.