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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About this Course
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Shareable Certificate
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Course 6 of 6 in the
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Intermediate Level
Approx. 11 hours to complete
English
Subtitles: English
Skills you will gain
Dimensionality ReductionUnsupervised LearningCluster AnalysisTime SeriesK Means Clustering
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 6 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 11 hours to complete
English
Subtitles: English
Offered by
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
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
10 videos
Introduction to Forecasting and Time Series Analysis11m
Pandas Time Series Notebook - Part 17m
Pandas Time Series Notebook - Part 210m
Pandas Time Series Notebook - Part 313m
Pandas Time Series Notebook - Part 49m
Time Series Decomposition4m
Decomposition Models9m
Decomposition Notebook - Part 17m
Decomposition Notebook - Part 27m
3 readings
Time Series Demo (Activity)10m
Time Series Decomposition Demo (Activity)10m
Summary/Review10m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz10m
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
13 videos
Stationarity Notebook - Part 17m
Stationarity Notebook - Part 27m
Stationarity Notebook - Part 314m
Nonstationarity Examples4m
Identifying Nonstationarity7m
Common Transformations6m
Time Series Smoothing6m
Smoothing Moving Averages5m
Smoothing Exponential Intro5m
Advanced Smoothing12m
Smoothing Notebook - Part 112m
Smoothing Notebook - Part 215m
3 readings
Stationarity Demo (Activity)10m
Time Series Smoothing Demo (Activity)10m
Summary/Review10m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz10m
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
9 videos
Useful Plots9m
ARMA Models Notebook - Part 110m
ARMA Models Notebook - Part 210m
ARIMA and SARIMA Models12m
SARIMA Prophet Notebook - Part 112m
SARIMA Prophet Notebook - Part 215m
SARIMA Prophet Notebook - Part 314m
SARIMA Prophet Notebook - Part 425m
3 readings
ARMA Models Demo (Activity)10m
SARIMA Prophet Demo (Activity)10m
Summary/Review10m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz10m
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.
3 hours to complete
8 videos (Total 70 min), 3 readings, 4 quizzes
8 videos
Deep Learning - Part 26m
Deep Learning - Part 34m
Deep Learning Notebook - Part 114m
Deep Learning Notebook - Part 211m
Survival Analysis and Censoring - Part 110m
Survival Analysis and Censoring - Part 28m
Survival Analysis Notebook8m
3 readings
Deep Learning for Forecasting Demo (Activity)10m
Survival Analysis Demo (Activity)10m
Summary/Review10m
3 practice exercises
Check for Understanding5m
Check for Understanding5m
End of Module Quiz10m
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.
Frequently Asked Questions
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:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
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