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Georgia Institute of Technology

Introduction to Analytics Modeling

Georgia Institute of Technology via edX

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

3.6 rating, based on 5 reviews

Start your review of Introduction to Analytics Modeling

  • Profile image for Diem Hoang
    Diem Hoang
    2
    Save your money to learn R somewhere else. I spent 40 hour in this course. Waste my time and money. didnt learn anything., The concept is very easy to understand The hard part is the coding and the TA is not very helpful. its $825 while linkedin...
  • Kshitij Jhamb 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...
  • Spalthoff Daniel 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....
  • Ashok Kumar
    2

    Ashok Kumar 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....
  • Leo Steeghs 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!

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