Andrew Ng's updated Machine Learning Specialization, the most recommended starting point for machine learning. It teaches the core algorithms with just enough maths and hands-on Python, and is beginner-friendly despite the intermediate label. If you are new to ML, start here.
Good for: Beginners to machine learning who want the best-regarded starting point.
Less suitable if: You already know the ML basics, or you want deep mathematical theory.
Requirements: A little Python and basic maths; beginner-friendly despite the label.
Realistic time: Around 94 hours across three courses; two to three months part-time.
About this course
The Machine Learning Specialization is Andrew Ng's updated three-course introduction to machine learning, rebuilt in Python. Most learners finish in about two to three months at a few hours a week. You can audit it free; the certificate runs on Coursera's ~$49/month plan.
What you'll learn
Build supervised models with linear and logistic regression
Train neural networks for classification tasks
Apply practical tips that make models actually work
Use unsupervised learning like clustering and anomaly detection
Build a simple recommender system
Understand the core maths intuitively, all in Python
This course includes
94h
On-demand video
Yes
Certificate
English
Language
What it costs
Free to audit on Coursera; the certificate needs a subscription, around $49 a month, with financial aid available. Finishing in a couple of months keeps the cost modest.
Comparison · LBS
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The certificate is issued through Coursera with DeepLearning.AI and Stanford. It is well regarded, but the coding practice and any projects you build matter most.
Last updated
Instructor
AN
Andrew Ng
Coursera instructor
Andrew Ng co-founded Coursera and Google Brain and is one of the most recognised teachers in machine learning. This specialization is the modern rebuild of the original course that introduced millions of people to the field.
It is the updated version. The classic 2012 course used Octave and MATLAB; this specialisation uses Python and modern tools, and is gentler and more current.
Yes. Despite the intermediate label, it is one of the most beginner-friendly ways into machine learning.
Start here. This covers core machine learning; the Deep Learning Specialization is the more advanced, neural-network follow-on.
Yes, audit it free on Coursera. The certificate needs a subscription, with financial aid available.
Just the basics. It keeps the maths approachable and focuses on intuition and hands-on practice.
Around 94 hours across three courses — two to three months part-time.