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Learner Reviews & Feedback for Specialized Models: Time Series and Survival Analysis by IBM

4.5

stars

126 ratings

About the Course

This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. You will learn how to find analyze data with a time component and censored data that needs outcome inference. You will learn a few techniques for Time Series Analysis and Survival Analysis. The hands-on section of this course focuses on using best practices and verifying assumptions derived from Statistical Learning. By the end of this course you should be able to: Identify common modeling challenges with time series data Explain how to decompose Time Series data: trend, seasonality, and residuals Explain how autoregressive, moving average, and ARIMA models work Understand how to select and implement various Time Series models Describe hazard and survival modeling approaches Identify types of problems suitable for survival analysis Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Time Series Analysis and Survival Analysis. What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Supervised Machine Learning, Unsupervised Machine Learning, Probability, and Statistics....

Top reviews

Apr 30, 2022

Excellenct course.

I could experience so many methodologies.

So tough to finish each project.

I really thank IBM and Coursera for this great course with just so small tuition fee.

May 6, 2021

A very well-structured course with useful techniques and detail guidelines. The Python code templates are also really useful when bringing into real-life problems.

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26 - 32 of 32 Reviews for Specialized Models: Time Series and Survival Analysis

By vikas v

•

Nov 22, 2020

Amazing Concepts explanations

By Dennis B

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Jun 24, 2022

Excellent!!!

By Vivek O

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Dec 27, 2021

Excellent!

By Bui V T

•

Mar 22, 2023

Very good

By Darius V

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Apr 12, 2024

Good introduction to Time Series forecasting. The Jupyter Notebooks are interesting and helpful, but the the video content is just the instructor reading off of slides or Jupyter notebooks. The video content is not the best use of time for learning, and the quizzes are 3 high level questions. 4/5 since the course does hit the main objectives.

By Zizhi W

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Sep 27, 2021

This course is good but not as good as the previous five courses in this series. I think the points need more explanation and it might be more suitable to extend this course to more weeks.

Moreover, one has to go through peer review. I really wait for a long time to get reviewed. Moreover, after I put 'my course is going to expire soon', someone just gave all zero to my assignment and I had to reloaded the work again and found new people reviewing it. This is really a terrible experience.

By krysten z

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Oct 16, 2020

not able to cancel the course.