IBM
Specialized Models: Time Series and Survival Analysis
IBM

Specialized Models: Time Series and Survival Analysis

Taught in English

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Mark J Grover
Miguel Maldonado

Instructors: Mark J Grover

14,194 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.5

(122 reviews)

Intermediate level
Some related experience required
11 hours (approximately)
Flexible schedule
Learn at your own pace

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Assessments

12 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.5

(122 reviews)

Intermediate level
Some related experience required
11 hours (approximately)
Flexible schedule
Learn at your own pace

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This course is part of the IBM Machine Learning Professional Certificate
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There are 4 modules in this course

This module introduces the concept of forecasting and why Time Series Analysis is best suited for forecasting, compared to other regression models you might already know. You will learn the main components of a Time Series and how to use decomposition models to make accurate time series models.

What's included

10 videos3 readings3 quizzes

This module introduces you to the concepts of stationarity and Time Series smoothing. Having a Time Series that is stationary is easy to model. You will learn how to identify and solve non-stationarity. Smoothing is relevant to you as it will help improve the accuracy of your models.

What's included

13 videos3 readings3 quizzes

This module introduces moving average models, which are the main pillar of Time Series analysis. You will first learn the theory behind Autoregressive Models and gain some practice coding ARMA models. Then you will extend your knowledge to use SARMA and SARIMA models as well.

What's included

9 videos3 readings3 quizzes

This module introduces two additional tools for forecasting: Deep Learning and Survival Analysis. In addition to AI and Machine Learning applications, Deep Learning is also used for forecasting. Survival Analysis is a branch of Statistics first ideated to analyze hazard functions and the expected time for an event such as mechanical failure or death to happen. Survival Analysis is still used widely in the pharmaceutical industry and also in other business scenarios with limited data related to censoring, the lack of information on whether an event occurred or not for a certain observation.

What's included

8 videos3 readings3 quizzes1 peer review

Instructors

Instructor ratings
4.4 (48 ratings)
Mark J Grover
IBM
13 Courses84,050 learners

Offered by

IBM

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4.5

122 reviews

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MH
4

Reviewed on Feb 25, 2021

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5

Reviewed on Dec 16, 2021

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Reviewed on Jan 4, 2022

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