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Introduction to Analytics Modeling

Georgia Institute of Technology via edX

4 Reviews 185 students interested

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Overview

Analytical models are key to understanding data, generating predictions, and making business decisions. Without models it’s nearly impossible to gain insights from data. In modeling, it’s essential to understand how to choose the right data sets, algorithms, techniques and formats to solve a particular business problem.

In this course, part of the Analytics: Essential Tools and Methods MicroMasters program, you’ll gain an intuitive understanding of fundamental models and methods of analytics and practice how to implement them using common industry tools like R.

You’ll learn about analytics modeling and how to choose the right approach from among the wide range of options in your toolbox.

You will learn how to use statistical models and machine learning as well as models for:

  • classification;
  • clustering;
  • change detection;
  • data smoothing;
  • validation;
  • prediction;
  • optimization;
  • experimentation;
  • decision making.

Taught by

Joel Sokol

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Reviews for edX's Introduction to Analytics Modeling
4.3 Based on 4 reviews

  • 5 star 25%
  • 4 stars 75%
  • 3 star 0%
  • 2 star 0%
  • 1 star 0%

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  • 1
Kshitij J
4.0 a year ago
by Kshitij completed this course, spending 10 hours a week on it and found the course difficulty to be hard.
I am about to complete the course as a verified learner, i found the course content to be very good and very well spread out.

Thumb's up-

->The details covered are very structured and well articulated,sometimes even some small tips from Prof Joel within the videos are very valuable to say the least.

->TA's associated with the program are very responsive and are more than willing to answer your doubts , i learned a lot from them .

-> Assignments and tests are usually very hard ,so its fun to look back and see the steep climb you made over th…
Was this review helpful to you? Yes
Spalthoff D
4.0 2 years ago
by Spalthoff completed this course, spending 20 hours a week on it and found the course difficulty to be very hard.
I just finished this course as a verified learner. The content is excellent (5 stars), but for two reasons my overall evaluation of the course is a 4 stars:

This is the first time this course is offered via edX, and there were many technical glitches. But course staff was very responsive, and I assume that these problems will be fixed in future versions of the course.

The course announcement wasn't clear about required knowledge and skills to take the course. Most homework requires proficiency in R.

A positive point was the very active Slack group of students, which helped a lot. (The edX forum, on the other hand, was difficult to use.)

Bottom line is, this course is extremely interesting, one of the best I have ever taken, very ambitious with the topics covered. You will enjoy the course if you have basic proficiency in R.
Was this review helpful to you? Yes
Ashok K
4.0 7 months ago
Ashok completed this course, spending 6 hours a week on it and found the course difficulty to be medium.
I found this course to be very well executed. While there were some technical difficulties at times but they were easily compensated by the ever responsive TAs, messaging board, office-hours etc.

The course does a great job of covering a lot of topics. Due to this reason some of the topics feel like glossed over but I guess that is more by design than overlook. If you are a beginner, then you will need to invest a lot of time reading material other than what is discussed in videos / assignments to get a decent understanding of the topics.

The course require familiarity with R. My R knowledge was rusty and hence I had to spend a lot of time for the first couple of assignments. I think it would be great if the course videos can spend some time in setting the expectations regarding the use of R in assignments.
Was this review helpful to you? Yes
Leo S
5.0 2 years ago
by Leo completed this course, spending 10 hours a week on it and found the course difficulty to be hard.
Very interesting for somebody new to statistics and R programmering like me. Nice teaching, homework is quite tough.. overall very good experience!
Was this review helpful to you? Yes
  • 1

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