Machine Learning for Beginners: Car Price Prediction

About this course

Are you curious about how machine learning works — but don't know where to start?

This beginner-friendly course is your perfect starting point. In this hands-on project, you'll build a real-world machine learning model to predict car prices using Python and Linear Regression.

Even if you're new to coding, data science, or machine learning, don’t worry! Every concept is explained in a simple and practical way, step by step.

What You'll Learn:

• Load and explore real-world data using pandas
• Perform exploratory data analysis (EDA) using Matplotlib and SeabornClean and pre-process data for machine learning
• Apply feature engineering and remove irrelevant columns
• Train a Linear Regression model using scikit-learn
• Evaluate model performance using MAE, MSE, and R² score
• Save the model and make predictions on new car data
• Understand the full machine learning workflow from start to finish

Tools Used:

• Pythonpandasmatplotlib & seabornscikit-learn (sklearn)joblib

By the end of this course, you’ll have built your own car price prediction model — a strong portfolio project to showcase in interviews, apply for internships, or boost your confidence as a future data scientist.

Explore the of machine learning!

No prior experience needed. Just bring your curiosity — and let's build your first ML project together!

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