Data Science at Scale - Capstone Project
Learn scalable data management, evaluate big data technologies, and design effective visualizations.This Specialization covers intermediate topics in data science. You will gain hands-on experience with scalable SQL and NoSQL data management solutions, data mining algorithms, and practical statistical and machine learning concepts. You will also learn to visualize data and communicate results, and you'll explore legal and ethical issues that arise in working with big data. In the final Capstone Project, developed in partnership with the digital internship platform Coursolve, you'll apply your
Created by: Bill Howe
Quality Score
Overall Score : 86 / 100
Course Description
Instructor Details
- 4.3 Rating
3 Reviews
Bill Howe
Bill Howe is the Director of Research for Scalable Data Analytics at the UW eScience Institute and holds an Affiliate Assistant Professor appointment in Computer Science & Engineering, where he leads a group studying data management, analytics, and visualization systems for science applications. Howe has received awards from Microsoft Research and honors for papers in scientific data management, and serves on a number of program committees, organizing committees, and advisory boards in the area, including the advisory board of the Data Science certificate program at UW. He holds a Ph.D. in Computer Science from Portland State University and a Bachelor's degree in Industrial & Systems Engineering from Georgia Tech.
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3.7 (53 Reviews)
Provider: Coursera
Time: 13h
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Reviews
By Alfonso A on 6-Sep-17
The topic and milestone-based schedule are great; you are free to take many decisions but still get enough guidance to avoid straying away from the project goal. Instructor and student commitment is a bit low; there is very little feedback in the forums and submissions are sometimes so shallow that add little value to the reviewer.
By Simy R on 2-Jan-17
An interesting problem to tackle. I really liked that you started with very raw data and needed to work on many cleaning methods. Good practice for real data science.
By Aref A on 10-Oct-16
This course introduces data science with a emphasis on large scale processing. The project was challenging and very interesting. Applying with I learnt throughout the specialisation to a real problem is very exciting.
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