What you'll be able to do
- Clean and analyze real datasets with Pandas and NumPy
- Visualize data and run EDA with Matplotlib and Seaborn
- Build and evaluate machine-learning models with scikit-learn
- Apply NLP basics and understand the deep-learning workflow
- Deploy a trained model and tune it for better performance
Before you start
- A laptop that can run Python and Jupyter / Anaconda
- Basic programming logic helps but is not required
- School-level maths comfort (no heavy theory needed)
Tools & technologies
How you'll learn
This course's public GitHub repo is shared when the next cohort opens —ask us for a preview and we'll send you the link.
The certificate you'll earn
- Issued on program completion, with your name, course and grade.
- Carries a unique certificate ID and QR code.
- Anyone can confirm it in seconds on ourcertificate verification page — recruiters included.
A practice-first, project-driven summer internship track into data science with Python. Start with Python essentials, then go hands-on with NumPy, Pandas, Matplotlib, and Seaborn for real data wrangling, visualization, and EDA. Move into machine learning with scikit-learn — regression, classification, clustering, PCA — then NLP, a taste of deep learning, and deploying a model with Flask. Three mini-projects and a final customer-churn capstone on real datasets.
Upcoming cohorts
New cohort dates are announced regularly — send an enquiry and we'll reserve you a seat in the next one.
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Course · Data Science
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Go from Python basics to training and evaluating real machine-learning models on real datasets.
- Foundation
- Classroom · Online (Live)
- New cohort announced soon