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
University of Washington
Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.
- 5 stars48.22%
- 4 stars32.03%
- 3 stars10.03%
- 2 stars5.50%
- 1 star4.20%
TOP REVIEWS FROM PRACTICAL PREDICTIVE ANALYTICS: MODELS AND METHODS
Its Hard! but AWESOME, some much info packed in a few lectures!
I enjoy this course. The delivery and the course topics were very interesting. I learnt a lot and peer reviewing other people assignments is a great learning opportunity .
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.
Nive that the course covered a broad range of topics.
And good to get pushed to do some kaggle competition and peer review.
About the Data Science at Scale Specialization
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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