Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.
About this Course
Skills you will gain
- 5 stars48.22%
- 4 stars32.03%
- 3 stars10.03%
- 2 stars5.50%
- 1 star4.20%
TOP REVIEWS FROM PRACTICAL PREDICTIVE ANALYTICS: MODELS AND METHODS
Excellent Lectures. Since the course is several years old the organization of some of the assignments needs updating. That's the only reason I gave it 4 instead of 5 stars.
Very nice assignments and content. You learn a lot when you complete all assignments.
Fantastic course! Excellent conceptual teaching for people who already know the subject but need some more clarity on how to approach statistical tests and machine learning.
Need some background in R or Python and the lectures are from around 2013. Most of the material is still relevant.
About the Data Science at Scale Specialization
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