Machine Learning Bootcamp: Python, Projects & Deployment

This is a complete, hands-on Machine Learning bootcamp designed to take you from Python basics to building and deploying real-world, production-ready ML applications.

You will learn Machine Learning the right way – starting with Python and essential math foundations, working with real datasets, building models, evaluating them correctly, and finally deploying ML systems on AWS.

Unlike theory-heavy courses, this bootcamp focuses on practical understanding, clean code, real projects, and real deployment workflows used in industry.

What you will gain from this course:

• Strong Python programming skills for Machine Learning
• Clear intuition for math behind ML including linear algebra, statistics, calculus, and probability
• Hands-on experience with data collection, EDA, and preprocessing
• Build and evaluate classification, regression, and unsupervised models
• Proper model validation, cross-validation, and optimization techniques
• Multiple real-world Machine Learning projects
• Convert notebooks into clean, production-style Python scripts
• Build ML APIs using FastAPI and UIs using Streamlit
• Deploy complete ML applications on AWS EC2
• Work on production-grade capstone projects you can showcase in your portfolio

Who this course is for:

• Beginners starting Machine Learning from scratch
• Students preparing for ML or data science roles
• Professionals transitioning into Machine Learning
• Developers who want to build and deploy real ML applications

No prior Machine Learning, Python or math background is required. Everything is explained step by step with intuition and hands-on examples.

By the end of this bootcamp, you will not just understand Machine Learning —

you will be able to build, deploy, and explain real ML systems with confidence.