Car Price Prediction in 1 Hr : Build an ML Model with Python

Learn how to clean data, apply encoding, and train ML models using Python — all in under 60 minutes.

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Car Price Prediction in 1 Hr : Build an ML Model with Python

Car Price Prediction in 1 Hr : Build an ML Model with Python udemy course free download

Learn how to clean data, apply encoding, and train ML models using Python — all in under 60 minutes.

Course Description:

Learn machine learning by building a real-world project — from start to finish — in just one hour.

This course offers a fast, focused, and practical introduction to machine learning using one of the most relatable examples: predicting car prices. You’ll work with real-world data and use industry-standard tools like Python, Pandas, Scikit-learn, and Google Colab to develop a complete machine learning pipeline. Best of all, there's no need to install anything — all work is done in the cloud.

This hands-on course is designed for:

  • Beginners who want to learn ML through practical application rather than theory

  • Developers curious about applying ML to real-world problems

  • Students looking to add a portfolio project

  • Anyone interested in exploring how machine learning models are trained and evaluated

Throughout the course, you’ll follow a structured, step-by-step process to build your car price prediction model. You’ll start with raw CSV data and end with a fully trained and tested ML model that can make predictions on unseen data.

You’ll learn how to:

  • Import and inspect real-world car pricing data

  • Clean and preprocess data using Pandas

  • Apply One Hot Encoding and Label Encoding to categorical variables

  • Train a Linear Regression model and evaluate its performance

  • Improve accuracy with a Random Forest Regressor

  • Use train_test_split to validate your model’s performance

  • Calculate error metrics like Mean Squared Error (MSE)

  • Use Google Colab to write, run, and share your code

By the end of the course, you will:

  • Understand the end-to-end machine learning workflow

  • Be comfortable using key tools in the Python ML ecosystem

  • Be able to apply what you've learned to your own datasets and problems

  • Have a completed, portfolio-ready machine learning project

This course is short by design — perfect for busy learners or those just getting started with ML. It emphasizes action over theory, with clear explanations and practical takeaways at every step.

Join now and take your first step into the world of machine learning — no fluff, no filler, just real results in under an hour.

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