Structured learning paths
Choose Structured learning paths on the welcome screen. Each path is taught with the tutor inside a real project:
- Web Foundations
- Backend APIs with Node
- Python for Data
- Git & Collaboration
- Debugging Mastery
- Data Structures & Algorithms
- Testing Mastery
- Databases & SQL
- Security Essentials
- Deployment & DevOps
- TypeScript
New to the IDE itself? Click Meet LoWisa in the menu bar for a narrated tour, or choose Learn LoWisa itself on the welcome screen: what each part of the workbench does, when to reach for it, and a lesson that proves you can.
Other ways to learn
- Generate your own path. Name any topic and the tutor designs a curriculum with auto-graded exercises.
- Mission-led learning. Fix a real product problem in a world you love, such as sports, music or games, and master the concepts behind it.
- Build from your YouTube creator. Paste one of their videos; the tutor pulls out every project they proposed and teaches you to build each one.
- Applied mathematics. Tune real simulations of queues, probability and optimisation, and build intuition for the maths that runs real systems.
Learning together: Classroom
Choose Classroom on the welcome screen to teach a live class, or join one with an invite code from your teacher.
On your phone too
The LoWisa phone app on Google Play and the App Store teaches the same way, with 37 programming languages, career paths and any topic you describe. A plan bought on the web works in both: activate it with the email you subscribed with. See Getting started with the phone app.
Frequently asked questions
What learning paths does the LoWisa IDE have?
Web Foundations, Backend APIs with Node, Python for Data, Git & Collaboration, Debugging Mastery, Data Structures & Algorithms, Testing Mastery, Databases & SQL, Security Essentials, Deployment & DevOps and TypeScript, plus paths you generate on any topic.
What is Applied mathematics in the LoWisa IDE?
A part of the IDE where you tune real simulations of queues, probability and optimisation and build intuition for the maths that runs real systems.