Your cart is empty.
Keep shopping
Machine Learning for Beginners: Car Price Prediction
Machine Learning for Beginners: Car Price Prediction
Build a real-world ML project in Python using pandas, sklearn & linear regression — no experience needed!
Created bysai kumar routhu
Last updated 7/2025
English
What you'll learn
- Understand how to use Linear Regression for predictive modeling in Python.
- Clean and preprocess data using Pandas and Scikit-learn.
- Train, evaluate, and improve a machine learning model using real-world car data.
- Export and test your trained ML model using Pickle and new data.
- Build an end-to-end machine learning project using Python. Explore data with visualizations using Matplotlib and Seaborn.
Explore related topics
Course content
5 sections • 14 lectures • 1h 12m total length
Requirements
- No prior machine learning experience needed! Basic knowledge of Python is helpful (like variables, loops, and functions). A computer with internet access and Jupyter Notebook installed (or Google Colab). Curiosity and willingness to learn data science step by step!
Description
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 Seaborn
Clean 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:
Python
pandas
matplotlib & seaborn
scikit-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!
Who this course is for:
- Beginners who want to start their machine learning journey with a real project. Python learners looking to apply their skills in data science. Students and hobbyists interested in predictive modeling. Anyone curious about car prices, data analysis, or building ML models from scratch. Freshers preparing for interviews or building ML portfolios.