Data Science Methodology

( 376 Reviews )

Created by: Alex Aklson

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Overall Score : 98 / 100

Course Description

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand.Accordingly, in this course, you will learn:- The major steps involved in tackling a data science problem.- The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.- How data scientists think!LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

Time: 7h

Instructor Details

Alex Aklson

4.9 Rating
376 Reviews

Alex Aklson, Ph.D., is a data scientist in the Digital Business Group at IBM Canada. Alex has been intensively involved in many exciting data science projects such as designing a smart system that could detect the onset of dementia in older adults using longitudinal trajectories of walking speed and home activity. Before joining IBM, Alex worked as a data scientist at Datascope Analytics, a data science consulting firm in Chicago, IL, where he designed solutions and products using a human-centred, data-driven approach. Alex received his Ph.D. in medical Engineering from the University of Toronto.

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Reviews

4.9

376 total reviews

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By Gloria W on 14-Dec-18

This could've been condensed down immensely, but I suppose it's something you deal with when sorting through data for data science.

By Nilanjan D on 23-Jan-19

Good course. Gives a sense of methodology and how to approach the research.

By Paulo H d S on 2-Feb-19

It is refreshing to see a data science course that clearly talks about the methodology (which is fundamental to thinking about the process) rather than the technology (which, while useful, but the lure of technology is often used sloppily without real underlying thinking and reflection.).

By BalÃƒÂ¡zs L on 30-Jan-19

The information is useful and relevant. But the labs are limited in their utility, since the student isn't actually doing any of the work, just following along in the example. The lab information could just as easily be presented in the video, and vice versa. So it isn't really a "hands on" activity for practice.

By Anupriya A on 30-Jan-19