This course is a fast-paced, hands-on project designed for intermediate learners who want to gain real-world experience in data science and machine learning. Instead of focusing on theory or basic programming, the course walks you through the complete lifecycle of a practical project—building a Fake News Detection system from scratch and deploying it for real-world use.
In under two hours, you will learn how to design and structure a data science project, collect and preprocess data, train a machine learning model, and evaluate its performance. Most importantly, you will understand how to take your model beyond experimentation and deploy it into a usable application.
The course is built for learners with limited computing resources and time, using cloud-based tools to simplify development and execution. By the end, you will not only have a working project but also a clear understanding of how real-world machine learning workflows operate.
If you already have a basic understanding of Python and machine learning concepts and want to move from learning to building, this course will help you bridge that gap quickly and effectively.