Predictive Data Analytics
The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling.
About the course
The course aims to give insights in fundamental concepts of machine learning for predictive analytics to provide actionable, i.e., better and more informed decisions in, forecasting. It covers the key concepts to extract useful information and knowledge from data sets to construct predictive modeling.
Introduction: overview of Predictive data analytics and Machine learning for predictive analytics.
Data exploration and visualization: presents case studies from industrial application domains and discusses key technical issues related to how we can gain insights enabling to see trends and patterns in industrial data.
Predictive modeling: consists of issues in construction of predictive modeling, i.e., model data and determine Machine learning algorithms for predicative analytics and techniques for model evaluation.
You will learn
- Select suitable machine learning algorithms to solve a given problem for predictive data analytics.
- Explore data and produce datasets suitable for analytical modeling.
- Basics of machine learning for predictive analytics
For Course Syllabus use course code DVA478 in the.
Shahina Begum, Senior Lecturer
+46 21 10 73 70
Mobyen Uddin Ahmed, Associate Professor
+46 21 10 73 69