Specialized Models Time Series and Survival Analysis

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.

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Syllabus

Syllabus - What you will learn from this course
Week 1
Introduction to Time Series Analysis
Week 2
Stationarity and Time Series Smoothing
Week 3
ARMA and ARIMA Models
Week 4
Deep Learning and Survival Analysis Forecasts

FAQ

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

What will I get if I subscribe to this Certificate?

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Reviews

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.

This is an excellent course covering large areas of Time Series analysis and is a must for any one intending to learn the topics with some detail.

Great course, very well taught and topics are useful for future applications

It is a good course to build foundation on the modeling of timerseries data. It will be good to add other lessons for anomaly detection on timeseries.