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.
Ce cours fait partie de la Nombre de Apprentissage automatique IBM Certificat Professionnel
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Cours 6 sur 6 dans le
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Niveau intermédiaire
Approx. 11 heures pour terminer
Anglais
Sous-titres : Anglais
Compétences que vous acquerrez
Dimensionality ReductionUnsupervised LearningCluster AnalysisTime SeriesK Means Clustering
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 6 sur 6 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 11 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
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.
Programme du cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
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 heures pour terminer
10 vidéos (Total 83 min), 3 lectures, 3 quiz
10 vidéos
Course Introduction2 min
Introduction to Forecasting and Time Series Analysis11 min
Pandas Time Series Notebook - Part 17 min
Pandas Time Series Notebook - Part 210 min
Pandas Time Series Notebook - Part 313 min
Pandas Time Series Notebook - Part 49 min
Time Series Decomposition4 min
Decomposition Models9 min
Decomposition Notebook - Part 17 min
Decomposition Notebook - Part 27 min
3 lectures
Time Series Demo (Activity)10 min
Time Series Decomposition Demo (Activity)10 min
Summary/Review10 min
3 exercices pour s'entraîner
Check for Understanding5 min
Check for Understanding5 min
End of Module Quiz10 min
3 heures pour terminer
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 heures pour terminer
13 vidéos (Total 110 min), 3 lectures, 3 quiz
13 vidéos
Stationarity Notebook - Part 17 min
Stationarity Notebook - Part 27 min
Stationarity Notebook - Part 314 min
Nonstationarity Examples4 min
Identifying Nonstationarity7 min
Common Transformations6 min
Time Series Smoothing6 min
Smoothing Moving Averages5 min
Smoothing Exponential Intro5 min
Advanced Smoothing12 min
Smoothing Notebook - Part 112 min
Smoothing Notebook - Part 215 min
3 lectures
Stationarity Demo (Activity)10 min
Time Series Smoothing Demo (Activity)10 min
Summary/Review10 min
3 exercices pour s'entraîner
Check for Understanding5 min
Check for Understanding5 min
End of Module Quiz10 min
3 heures pour terminer
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 heures pour terminer
9 vidéos (Total 117 min), 3 lectures, 3 quiz
9 vidéos
Useful Plots9 min
ARMA Models Notebook - Part 110 min
ARMA Models Notebook - Part 210 min
ARIMA and SARIMA Models12 min
SARIMA Prophet Notebook - Part 112 min
SARIMA Prophet Notebook - Part 215 min
SARIMA Prophet Notebook - Part 314 min
SARIMA Prophet Notebook - Part 425 min
3 lectures
ARMA Models Demo (Activity)10 min
SARIMA Prophet Demo (Activity)10 min
Summary/Review10 min
3 exercices pour s'entraîner
Check for Understanding5 min
Check for Understanding5 min
End of Module Quiz10 min
3 heures pour terminer
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 heures pour terminer
8 vidéos (Total 70 min), 3 lectures, 4 quiz
8 vidéos
Deep Learning - Part 26 min
Deep Learning - Part 34 min
Deep Learning Notebook - Part 114 min
Deep Learning Notebook - Part 211 min
Survival Analysis and Censoring - Part 110 min
Survival Analysis and Censoring - Part 28 min
Survival Analysis Notebook8 min
3 lectures
Deep Learning for Forecasting Demo (Activity)10 min
Survival Analysis Demo (Activity)10 min
Summary/Review10 min
3 exercices pour s'entraîner
Check for Understanding5 min
Check for Understanding5 min
End of Module Quiz10 min
À propos du Nombre de Apprentissage automatique IBM Certificat Professionnel
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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