Machine Learning Specialization DeepLearning

The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization 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 to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.)
By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.

Coursera

Stanford University,DeepLearning.AI

Advanced Learning Algorithms (Coursera)

Data Science

Expand your knowledge in machine learning by diving into 'Advanced Learning Algorithms'. This course will guide you through building and training complex neural networks using TensorFlow for effective multi-class classification tasks. You'll also learn best practices for developing machine learning models that generalize well to real-world data and scenarios, as well as explore decision trees and ensemble methods like random forests and boosted trees.

Jun 1st 2026

4 Weeks

Algorithms Machine Learning Neural Networks

Coursera

Stanford University,DeepLearning.AI

Supervised Machine Learning: Regression and Classification (Coursera)

Data Science

Dive into the world of Supervised Machine Learning with our introductory course designed to equip you with essential skills in model building and training. This course will guide you through constructing and refining regression and classification models using Python's powerful libraries such as NumPy and scikit-learn, enabling you to tackle prediction and binary classification tasks effectively.

Jun 1st 2026

3 Weeks

Python Machine Learning Regression

Page 1