BeginnerPython
From zero to production-grade Python.
Python for Data Science
Real notebooks, real datasets, real mentorship โ every concept paired with hands-on coding.
โน3,000 โน4,999Explore โ
A mentor-led path through AI, Machine Learning, Deep Learning and Statistics โ built so every concept compounds into real, shippable skill.
Learners, mentors and researchers collaborating across time zones, not isolated in separate cohorts.
Research-grade depth at a price that doesn't gate learning behind privilege.
Curriculum that respects academic rigor while staying honest about how production AI actually ships.
Every track ends in something you shipped โ not just something you watched.
Tracks are sequenced like a research curriculum: each idea leans on the last, every notebook reinforces the theory above it, and mentor feedback closes the loop before a gap can grow.
week 4 ยท gradient descent
def train(model, data):
loss = forward(model, data)
grads = backward(loss)
model = update(model, grads)
return model
Every formula sits next to the function that implements it.
1:1 calls with mentors who've published and shipped.
Weekly live classes with your cohort, not pre-recorded loops.
Stuck on a stack trace? A mentor opens your notebook live.
Git, Docker, LaTeX โ the stack working engineers actually use.
Premium curriculum, priced like it's meant to be used.
Real notebooks, real datasets, real mentorship โ every concept paired with hands-on coding.
Probability, inference, hypothesis testing and Bayesian thinking โ the backbone every ML engineer needs.
End-to-end machine learning โ from feature engineering to MLOps. Build six production-grade models with mentorship.
From convolutions to transformers โ train and fine-tune modern architectures with PyTorch.
The scientific computing stack used by working researchers and labs, taught end-to-end.
Personalised research mentorship โ from idea to submission, with weekly 1:1 mentor calls.
From your first line of Python to your first AI paper.
Code fluency
Mathematical intuition
Build & deploy models
Neural & transformer mastery
Reproducible research
"We built the curriculum we wished had existed when we were learning this ourselves โ depth over shortcuts, code over slides, mentorship over a passive video feed."
"The deep learning track is the reason I finally felt ready to interview for ML roles. The mentor calls made the difference."
"My mentor pushed me to turn a class project into an actual submission. Having someone in your corner changes everything."
"The most balanced AI curriculum I've used โ never too theoretical, never just copy-paste code."
"I tell every student I mentor to start here. Strong fundamentals at a price that actually makes sense."
Join a cohort of learners building the AI products and research of tomorrow.