Overview:

This path introduces learners to core ML concepts and workflows, preparing them for specialized ML applications across career paths.

Who it’s for:

Beginners who want to understand the ML pipeline and gain hands-on experience building their first model.

What you’ll learn:

• What machine learning is and how it works

• Categories of ML: supervised, unsupervised, reinforcement

• Model training, evaluation, and improvement

• Key tools: scikit-learn, pandas, matplotlib

• Basic algorithms like linear regression and k-means

• Intro to datasets and data preprocessing

What you’ll build:

• A mini-project: Predict housing prices using linear regression

  • Understand the problem and clean the dataset

  • Perform exploratory data analysis

  • Train a linear regression model

  • Evaluate model performance

  • Visualize predictions