Machine Learning Projects in Python (2026)

Machine learning projects scored on data you cannot see: churn and credit risk models, predictive maintenance, NLP triage, forecasting and segmentation, built with pandas and scikit-learn.

9 projects: 3 intermediate, 6 advanced. Every step is checked as you go, an AI mentor helps when you are stuck, and you finish with a verifiable certificate.

Machine learning projects

  1. Churn Prediction with scikit-learn: Scored on Customers You Can't See — Build a churn model in pandas and scikit-learn, catch a leaky feature, and get scored on customers you can't see. Then direct your AI through the same job and catch its mistakes. (advanced · $2)
  2. Classical Machine Learning: From Regression to Ensembles — A story-driven scikit-learn course where a new data scientist at a fictional regional ISP builds regression, tree, ensemble, SVM, and clustering models end to end to solve real subscriber churn. (intermediate · $1.25)
  3. Customer Segmentation in Python: RFM Scores and k-Means Clustering — Segment an online store's customers with pandas and scikit-learn: RFM scores, named segments and k-means clusters. Then direct your AI through the same job and catch its mistakes. (advanced · $2)
  4. Pay-Equity Audit in Python: Raw Gap, Regression and a Remediation Budget — Audit a company's pay for gender equity with pandas and statsmodels: the raw gap, a regression that compares like with like, and a remediation budget. Then direct your AI through the audit. (advanced · $2)
  5. Sales Forecasting in Python: Beat the Baselines on a Hidden Future — Turn three years of messy daily sales into an honest weekly demand forecast with pandas and NumPy, backtest it against baselines, then direct your AI through the same job and catch its mistakes. (advanced · $2)
  6. Card Fraud Detection in Python: Imbalanced Classes, Precision-Recall and a Cost-Based Threshold — Build a card fraud model in pandas and scikit-learn, choose a cutoff in rupees, and get scored on transactions you can't see. Then direct your AI through the same job and catch its mistakes. (advanced · $2)
  7. Credit Risk Scorecard in Python: WOE, IV and a PD Model, Scored on Applicants You Can't See — Build a bank-style credit scorecard for an NBFC in Python: WOE, IV, a logistic PD model, Gini, KS and points, scored on hidden applicants. Then direct your AI through it. (advanced · $2)
  8. Predictive Maintenance in Python: Rolling Features, Anomaly Alerts and Failures You Can't See — Build a 24-hour motor failure warning with pandas and scikit-learn: rolling features, a rule-based alert, a model scored on hidden breakdowns. Then direct your AI through it and catch its mistakes. (intermediate · $1.25)
  9. Support Ticket Triage with NLP: TF-IDF and a Linear Model, Scored on Tickets You Can't See — Build a support-ticket router in Python: clean customer text, build TF-IDF features, train a linear model, get graded on hidden tickets, then direct your AI through it and catch its mistakes. (intermediate · $1.25)

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Frequently asked questions

What makes a machine learning project stand out?

Honest evaluation. Projects here are scored on held-out data you never see, so a model that only memorises the training set does not pass.

Do I need to install anything for these machine learning projects?

Most projects run in labs inside your browser (SQL, Excel, Python, Power BI, Git and more). Cloud projects say up front when they use your own AWS account or a simulator instead.

How is a Bartman project different from a tutorial?

You do the work yourself, step by step. Each step is checked automatically, and an AI mentor helps when you are stuck, so you finish with work you can show rather than a video you watched.

Do I get a certificate?

Yes. Finishing a project earns a certificate with its own ID that anyone can verify on bartman.ai.

What is Bartman?

Bartman (bartman.ai) is a learning platform where you build real projects with an AI mentor, practise in free browser labs, take mock tests and practice exams, and run job simulations. It was founded in 2025 and is based in Hyderabad, India.

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