Labs were incredibly useful as a practical learning tool which therefore helped in the final assignment! I wouldn't have done well in the final assignment without it together with the lecture videos!



Machine Learning with Python
This course is part of multiple programs.


Instructors: Joseph Santarcangelo
Access provided by South Mediterranean University
621,022 already enrolled
(17,987 reviews)
Recommended experience
What you'll learn
Explain key concepts, tools, and roles involved in machine learning, including supervised and unsupervised learning techniques.
Apply core machine learning algorithms such as regression, classification, clustering, and dimensionality reduction using Python and scikit-learn.
Evaluate model performance using appropriate metrics, validation strategies, and optimization techniques.
Build and assess end-to-end machine learning solutions on real-world datasets through hands-on labs, projects, and practical evaluations.
Skills you'll gain
Details to know

Add to your LinkedIn profile
See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from IBM

Why people choose Coursera for their career




Learner reviews
17,987 reviews
- 5 stars
75.90%
- 4 stars
18.63%
- 3 stars
3.45%
- 2 stars
0.99%
- 1 star
1.02%
Showing 3 of 17987
Reviewed on May 25, 2020
Reviewed on Jun 24, 2020
This course walks us through the fundamentals of machine learning methods. The capstone project is very useful for those who have previous knowledge of machine learning and Python programming.
Reviewed on Jun 3, 2020
In peer graded assignments, if someone is grading any peer below passing criteria then it must be compulsory to let the learner know his mistakes or shortcomings because of which he does not graded.