Learn with SciMigo MVP
Build a private question bank from pasted or uploaded material, practice one problem at a time, and learn through grounded chat, attempt analysis, and persistent progress.
Build courses. Learn with an AI tutor that remembers.
SciMigo is becoming a shared STEM learning workspace: educators turn source material into structured courses, while students learn through grounded chat, practice, and persistent progress.
66+ generated lessons · 4 showcase courses · learning MVP in development
Two ways into the same learning system
Teachers create and guide the course. Students study with an AI tutor that knows the material and builds a record of their learning.
Teach with SciMigo
Turn notes, PDFs, worksheets, and outlines into structured lessons. Publish a course, guide discussion, and see where learners need help.
Supporting capability
Visual storytelling when a concept needs more than slides
Course creators can add precise math animation or short cinematic STEM illustrations and historical microdramas. Both remain supporting capabilities inside Studio, not separate product paths.
For educators: start from real teaching material
PromptPDFLaTeXMarkdownImage/screenshot
From course material to a continuous learning loop
The course, tutor, practice, and learning record stay connected instead of becoming separate tools.
1
Create the course
An educator turns trusted source material into lessons, readings, examples, and practice.
2
Publish a path
Organize concepts and modules into a course students can join and resume.
3
Learn with context
The tutor answers from the current lesson, problem, and course knowledge base.
4
Build progress
Attempts, misconceptions, and mastery evidence shape what the student should do next.
Curated learning pilots
Courses designed to prove the learning experience
We are curating a small launch catalog where grounded tutoring, practice, and learning memory materially improve the outcome.
AI Foundations for High School
Understand, use, question, and build with AI through responsible, project-based learning.
Practical AI for Every Major
Research, analyze, create, and verify with AI through examples adapted to the learner’s field.
Quant Interview Math
Import a personal question collection, then practice probability, expected value, mental math, and market making with adaptive analysis.
Math Foundations for AI
Connect calculus, linear algebra, probability, and optimization to modern machine learning.
These are product directions, not a finished catalog. Early pilots will start small, measure learning loops and return visits, and expand only when the evidence is strong.
Proof from the production pipeline
Real generated courses, not mockups. Open the showcase to inspect the deck viewer, lesson structure, and AI tutor experience.
Structure and Interpretation of Computer Programs
This is demanding material—and that's why it works. Master the fundamental ideas of computation that shaped generations of programmers.
Linear Algebra for AI
Master the language of AI: vectors, matrices, transformations, and eigenvalues -- with Python code to ground every concept. From NumPy basics to LoRA fine-tuning and mechanistic interpretability.
Meta System Design Interview
What Meta actually tests, how it evaluates, and how to think at Staff level. 27 episodes covering distributed systems fundamentals, 13 real Meta-style design problems, and capstone mock interviews.
ML & AI System Design for Staff Engineers
14 episodes covering ML infrastructure, AI-era systems, and Staff-level architectural thinking — feature stores, model serving, training platforms, vector search, LLM serving, RAG, and AI gateway design.
One course space, different roles
Students
Learn with a tutor that knows the course, remembers prior work, and recommends a concrete next step.
Educators
Create, publish, and improve structured courseware from the material you already trust.
Classes and cohorts
Bring learners, teachers, and AI into grounded discussion around the same lessons and problems.
Frequently asked questions
What is SciMigo?
SciMigo is a STEM learning workspace for creating structured lessons and studying course material with context-aware AI. Its teaching studio is available in early access, while its personal practice and learning-memory tools are in active development.
How is SciMigo different from a general AI chatbot?
SciMigo keeps the lesson, reading, problem, and study history connected. The goal is a grounded learning loop: study specific material, ask or attempt something, receive feedback, record evidence, and continue with a concrete next step.
Can educators create STEM lessons from their own material?
Yes. In early access, educators can start from a prompt or source material such as PDFs, worksheets, Markdown, LaTeX, and images, then review a structured lesson before adding narration or video.
Is the student practice workspace available now?
The course showcase and course-grounded tutor are available today. Private question banks, attempt analysis, persistent progress, and personalized next steps are being built as focused MVP pilots.
Help shape a better way to teach and learn STEM.
Explore a real generated lesson or open the teaching studio. The student learning MVP is the next layer.