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.
This course is part of the IBM Machine Learning Professional Certificate
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Course 6 of 6 in the
Intermediate Level
Approx. 11 hours to complete
English
Subtitles: English
Skills you will gain
Dimensionality ReductionUnsupervised LearningCluster AnalysisTime SeriesK Means Clustering
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 6 of 6 in the
Intermediate Level
Approx. 11 hours to complete
English
Subtitles: English
Offered by
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Syllabus - What you will learn from this course
2 hours to complete
Introduction to Time Series Analysis
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.
2 hours to complete
10 videos (Total 83 min), 3 readings, 3 quizzes
3 hours to complete
Stationarity and Time Series Smoothing
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.
3 hours to complete
13 videos (Total 110 min), 3 readings, 3 quizzes
3 hours to complete
ARMA and ARIMA Models
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.
3 hours to complete
9 videos (Total 117 min), 3 readings, 3 quizzes
3 hours to complete
Deep Learning and Survival Analysis Forecasts
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.
3 hours to complete
8 videos (Total 70 min), 3 readings, 4 quizzes
Reviews
TOP REVIEWS FROM SPECIALIZED MODELS: TIME SERIES AND SURVIVAL ANALYSIS
by MBMay 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.
by GSMay 15, 2021
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.
by RTApr 7, 2021
Good course with some useful tips, the Survival part of the course was particularly interesting.
by MHFeb 25, 2021
Not much details but good as an overview on the topic
About the IBM Machine Learning Professional Certificate
Machine Learning is one of the most in-demand skills for jobs related to modern AI applications, a field in which hiring has grown 74% annually for the last four years (LinkedIn). This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Machine Learning and leverage the main types of Machine Learning: Unsupervised Learning, Supervised Learning, Deep Learning, and Reinforcement Learning. It also complements your learning with special topics, including Time Series Analysis and Survival Analysis.
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