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Machine Learning Specialization

Comprehensive machine learning course covering supervised learning, unsupervised learning, and best practices. Learn from Andrew Ng, one of the world's leading AI experts.

Stanford Online
4.9(4200K reviews)
4.2M students
Enroll Now (Free)

Course Info

Duration11 weeks
Students Enrolled4.2M+
CertificateYes
CostFree

Our Verdict: Highly Recommended

Machine Learning Specialization is one of the best Machine Learning courses available. With a 4.9/5 rating from 4.2M+ students and curriculum designed by Stanford Online, this course delivers exceptional value. Perfect for beginner learners looking to break into AI or level up their skills.

9/10 Overall ScoreBased on curriculum, outcomes, and student feedback

Pros & Cons

Pros

  • Taught by industry leaders with real-world experience
  • Hands-on projects you can add to portfolio
  • Active community and forum support
  • Certificate recognized by employers
  • Completely free to audit

Cons

  • Moves quickly - not ideal for absolute beginners
  • Assignments can be time-consuming (10-15 hrs/week)
  • Some lectures feel dated (recorded 2-3 years ago)

Detailed Curriculum

Weeks 1-2

Introduction & Foundations

8 hours
  • Python for ML
  • NumPy & Pandas
  • Data Visualization
  • Statistics Basics
Weeks 3-5

Supervised Learning

12 hours
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forests
  • SVM
Weeks 6-8

Neural Networks & Deep Learning

15 hours
  • Neural Networks Basics
  • Backpropagation
  • CNNs
  • RNNs
  • Optimization
Weeks 9-10

Advanced Topics & Capstone

10 hours
  • Unsupervised Learning
  • Reinforcement Learning
  • ML in Production
  • Final Project

Career Outcomes & ROI

$15-30K
Avg Salary Increase
68%
Career Change Rate
3-6 mo
Time to New Job

Where Graduates Work

GoogleMetaAmazonMicrosoftStartupsConsulting

Student Reviews

4.9/ 5
Sarah M.
ML Engineer @ Google

This course transformed my career. Went from $85K to $148K after completing it. The projects were hands-on and directly applicable to my job interviews.

2 months ago
James K.
Data Scientist @ Startup

Great content but moves fast. If you're a complete beginner, start with Python basics first. Otherwise, it's excellent.

1 month ago
Priya S.
Career Changer

Best investment I made. Took 3 months to complete while working full-time. Landed my first ML role 2 months after finishing.

3 weeks ago
Read All 4200K+ Reviews →

Frequently Asked Questions

Is Machine Learning Specialization worth it?
Yes, especially if you're serious about Machine Learning. With 4.2M+ students and a 4.9/5 rating, it's proven to deliver results. Plus, it's completely free to audit.
Do I need programming experience?
No, this course starts from basics. However, familiarity with basic programming concepts will help you move faster.
How long does it take to complete?
The course is designed for 11 weeks, but most students complete it in 2-3 months while working full-time (10-15 hours/week commitment).
Will I get a job after this course?
The course alone isn't enough. You need to build 3-5 strong portfolio projects, practice coding interviews, and apply to 50-100 jobs. But this course gives you the foundational knowledge you need.

Skills You'll Master

Python
TensorFlow
Linear Regression
Neural Networks
Deep Learning

Ready to Start?

Freeto audit
Enroll Now
  • 4.2M+ students enrolled
  • Shareable certificate
  • Lifetime access
  • Free to audit

Pro Tip

Even though it's free, treat it seriously. Set a schedule and stick to it. Completion rates are only 15%.

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