This course just gave me substantial and valuable knowledge on ml algorithms and how to apply it using python. As a result, it was a benefiting journey for me. Thanks a lot for such a course.
Machine Learning with Python
Machine Learning with Python
This course is part of multiple programs.
Instructors: Joseph Santarcangelo
Access provided by Chula Engineering
609,043 already enrolled
4.7
(17,889 reviews)
Intermediate level
Recommended experience
Flexible schedule
1 hour to complete
Learn at your own pace
94%
Most learners liked this course
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
- Scikit Learn (Machine Learning Library)
- Machine Learning Algorithms
- Supervised Learning
- Unsupervised Learning
- Applied Machine Learning
- Dimensionality Reduction
- Python Programming
- Regression Analysis
- Machine Learning
- Predictive Modeling
- Classification And Regression Tree (CART)
- Feature Engineering
- Statistical Analysis
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
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This course is available as part of
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Learner reviews
4.7
17,889 reviews
- 5 stars
75.89%
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Showing 3 of 17889
HR
5
Reviewed on Sep 5, 2021
RV
5
Reviewed on Jan 14, 2025
good course , some part is typical more statistical part shown, even i have good understanding of ML , so new learner will find little typical. rest tutor voice and language is understandable.
RN
5
Reviewed on May 25, 2020
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!
