Overview:

This path prepares you to build scalable and performant ML models and systems for deployment in real-world applications.

Who it’s for:

Those who want to go beyond theory and learn how to build and deploy ML systems in production environments.

What you’ll learn:

• Supervised and unsupervised ML techniques

• Model training, tuning, and validation

• Advanced model evaluation metrics

• Feature engineering and model optimization

• Model deployment with tools like Flask and FastAPI

• Introduction to MLOps, pipelines, and version control

• Working with cloud platforms and containers (intro level)

What you’ll build:

• End-to-end ML applications, such as:

  • Fraud detection system

  • Sentiment analysis tool

  • Image classifier

• Deployed ML model using an API