Machine Learning

A focused, job-ready ML foundation

Python through classical Machine Learning, with deployed models and real projects — the essential groundwork before deep learning or GenAI.

This is a five-phase, focused foundation: Python programming, data analysis and engineering (NumPy, Pandas, SQL/NoSQL), statistics and feature engineering, classical machine learning (regression, classification, ensembles, clustering), and finally model deployment and end-to-end projects. It’s deliberately scoped to classical ML — for deep learning, Generative AI and Agentic AI, the Data Science & Generative AI course continues where this one ends.

• Classical ML, done properly: regression, regularization, SVM, ensembles (Random Forest, XGBoost) and clustering.
• Deployment included: serving models as APIs with FastAPI/Flask, Docker basics, and deploying to AWS.
• Real project portfolio: customer churn, loan-default prediction, network intrusion detection, and a Supabase + Streamlit data app.

Lock in Early Bird pricing

Early Bird pricing is available for a limited time — the Regular price applies once the current cohort fills up.

What You Will Learn

Course Curriculum

16 modules — click a module to see what’s inside.

Depth over hype

The same teaching philosophy across every NavAiEra course — explained simply, then taken all the way to the bottom.

Skills You Will Acquire