Supervised Machine Learning: Regression and Classification

DeepLearning.AI is a specialist online education platform founded in 2017 that focuses on practical, industry-relevant training in artificial intelligence and machine learning. Designed for learners at multiple levels, its courses emphasize hands-on projects, clear conceptual foundations and tools commonly used in industry. The platform’s flexible online format makes it accessible to professionals and students worldwide who want to build skills without relocating.

Courses and specializations are structured to help learners develop applied portfolios, with real-world assignments, code notebooks and community review. Collaboration with leading practitioners ensures content remains current with industry practice, and certificate programs help demonstrate competencies to employers. The platform also supports career transitions, offering guidance on interviewing for technical roles and connecting learners with opportunities to showcase their work.

For international learners seeking concentrated, practice-oriented AI education, DeepLearning.AI provides a clear route to upskill quickly and build demonstrable expertise. Its global learner community, modular course design and emphasis on project-based learning make it a pragmatic choice for those aiming to enter research, product or engineering roles in the AI ecosystem.

This program is a non-degree course in Supervised Machine Learning, taught in English and offered by DeepLearning.AI in California. It's perfect for those who want to learn the fundamentals of machine learning and build real-world AI applications. The program lasts several weeks and helps you master key concepts and gain practical know-how.

The curriculum includes building machine learning models in Python using popular libraries like NumPy and scikit-learn. You'll learn to build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression. The program is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI.

After completing this program, you can pursue careers like Machine Learning Engineer, Data Scientist, AI Researcher, Business Intelligence Developer, or Data Analyst. You'll work with top employers in the tech industry, using your skills to build and train machine learning models, evaluate and tune models, and take a data-centric approach to improving performance.