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Specialized Models: Time Series and Survival Analysis
Master time series analysis and survival modeling for advanced machine learning forecasting techniques.
Course Cost
₹ 2,699
Intermediate
Skill Level
10 Hours
Self-paced lessons
This course delves into specialized machine learning models for time series analysis and survival analysis. Students will learn forecasting techniques, including decomposition models, stationarity concepts, and time series smoothing. The curriculum covers ARMA, ARIMA, and SARIMA models, as well as deep learning approaches for forecasting. Additionally, the course introduces survival analysis for analyzing censored data and hazard functions. Through hands-on projects and best practices in statistical learning, learners will gain practical skills in implementing these advanced modeling techniques for real-world applications in various industries.
15,545 Enrolled
English
What you'll learn
Identify common modeling challenges with time series data
Explain how to decompose time series data into trend, seasonality, and residuals
Understand and implement autoregressive, moving average, and ARIMA models
Select and apply appropriate time series models for various scenarios
Describe hazard and survival modeling approaches
Identify types of problems suitable for survival analysis
Apply deep learning techniques to forecasting problems
Gain hands-on experience with time series and survival analysis tools in Python
Skills you'll gain
This course includes:
6.3 Hours PreRecorded video
12 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
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There are 4 modules in this course
This course provides a comprehensive exploration of specialized machine learning models, focusing on time series analysis and survival analysis. Students will learn advanced forecasting techniques, including decomposition models, stationarity concepts, and time series smoothing. The curriculum covers ARMA, ARIMA, and SARIMA models, as well as deep learning approaches for forecasting. Additionally, the course introduces survival analysis for analyzing censored data and hazard functions. Through hands-on projects and best practices in statistical learning, learners will gain practical skills in implementing these advanced modeling techniques for real-world applications in various industries, such as finance, healthcare, and manufacturing.
Introduction to Time Series Analysis
Module 1 · 2 Hours to complete
Stationarity and Time Series Smoothing
Module 2 · 2 Hours to complete
ARMA and ARIMA Models
Module 3 · 2 Hours to complete
Deep Learning and Survival Analysis Forecasts
Module 4 · 3 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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1,16,700
Students
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Courses
4.4
49
Reviews
1,16,700
Students
5
Courses
Frequently asked Questions
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