Intro to Machine Learning

About this course

Machine learning powers everything from recommendation systems to fraud detection — and this Kaggle course teaches you to build your first ML models hands-on. You'll learn decision trees and random forests, two of the most intuitive and powerful algorithms in data science, using real datasets in interactive Kaggle notebooks. Kaggle, owned by Google, is trusted by millions of data scientists and is where serious ML practitioners sharpen their skills.

What you'll learn

• How to prepare data and handle missing values for machine learning models
• Build and train decision tree models to make predictions on real data
• Understand how random forests improve upon single decision trees through ensemble learning
• Evaluate your models using metrics like accuracy and make decisions about model performance
• Write Python code in Kaggle notebooks to load datasets and train models end-to-end
• Tackle real-world prediction problems (like house prices) using structured data
• Gain confidence to move from theory to actually building working machine learning systems

Who this is for

This course is ideal if you're curious about how machine learning actually works and want to stop watching tutorials and start building. You don't need to be a math genius or a professional programmer — you just need to be willing to learn by doing.

• Students — gain hands-on ML experience to stand out in campus placements and tech interviews at companies like TCS, Infosys, and HCL
• Career-changers and self-taught learners — build a concrete portfolio project and develop job-ready skills without formal education

Prerequisites

None — this course is beginner-friendly. Basic comfort with Python is helpful (variables, loops, functions) but you can learn as you go. No statistics or advanced math required.

Why this matters for Indian learners

Machine learning skills command premium salaries in India. Data scientists and ML engineers with portfolio projects earn 12–18 LPA starting out, and the demand is explosive across IT services, startups, and BFSI sectors. This course gives you the practical foundation to qualify for those roles. Whether you're aiming for roles at IT majors like Wipro and Tech Mahindra or AI-native companies like Unacademy and Vedantu, employers want to see that you can actually build and evaluate models — not just recite theory.

Frequently asked questions

Is this course really free?

Yes, completely free. Kaggle offers this course at no cost. You access all lessons and coding notebooks for free. If you want a certificate for your resume, that's also included at no charge.

How long will it take to complete?

The course is structured to take about 3 hours of active learning. We'd suggest spending 1–2 hours per session over 2–3 weeks, giving yourself time to absorb concepts and experiment with the code between lessons. Hands-on learning works best when you're not rushing.

Will I get a certificate?

Yes. After completing all lessons and the final project, Kaggle will issue a course completion certificate you can share on LinkedIn and in job applications. It's a credible signal that you've learned these skills on one of the world's most respected data science platforms.