"Turn raw, chaotic data into decisions that move businesses — the way real data scientists actually do it."
What You'll Do
Data science isn't about running models on Kaggle datasets. It's about sitting with a business problem, finding the right data, making it usable, building something predictive or explanatory, and communicating what you found to people who need to act on it. This program puts you through that full cycle — on real data, inside a real team, with a mentor who's worked in the field. You won't be graded on accuracy scores. You'll be evaluated on whether your work was useful.
Weekly Sync — one team meeting to review findings, align on next steps, get mentor input.
Async Work — analysis pushes to GitHub, discussed over Slack. Every module feeds the team's final deliverable.
✓ Statistics and probability for data science
✓ Data collection, cleaning and preprocessing
✓ Exploratory data analysis — patterns before modeling
✓ Hypothesis testing and statistical inference
✓ Supervised learning — regression and classification
✓ Unsupervised learning — clustering and dimensionality reduction
✓ Model building, evaluation and optimization
✓ Data storytelling for technical and non-technical audiences
✓ Time series analysis and forecasting basics
✓ End-to-end data science project lifecycle
Your team takes a real-world business dataset — e-commerce, healthcare, finance or logistics — and delivers a complete analysis with a predictive model and a presentation-ready insight report. You own a specific module. The final deliverable is reviewed and signed off by your mentor.
The data is real and messy. The problem is ambiguous. The team is depending on your module. The mentor isn't giving you answers — they're asking better questions. That pressure, that ambiguity, that accountability — that's exactly what data science at a company feels like.
Transform raw data into impactful insights and drive business decisions.
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