Build a Learning Habit
Download Class Central's free printable study calendar
Download for Free
ABOUT THE COURSE:
The course addresses the challenges often encountered when determining the characteristics of observational data and events. Statistical methods and Machine learning methods play a vital role in understanding the data characteristics and leading to data-driven solutions for many engineering challenges. Initially, the course begins with the basics of probability and statistics related to observations and events, and subsequently models them through random variables. A brief introduction to joint distribution (modelling) through copula is also included in the course for the modelling of joint distribution. The course also covers the joint and conditional distribution of events, which eventually leads to formulating probabilistic solutions for existing challenges across the domain. Furthermore, an introduction to machine learning models and their working principles will help in understanding the suitability of data-driven models and assessing their performance.
INTENDED AUDIENCE: Academician, students, Industrial Personnel
PREREQUISITES: Basic Knowledge of Probability and Statistics
INDUSTRY SUPPORT: Mathworks
The course addresses the challenges often encountered when determining the characteristics of observational data and events. Statistical methods and Machine learning methods play a vital role in understanding the data characteristics and leading to data-driven solutions for many engineering challenges. Initially, the course begins with the basics of probability and statistics related to observations and events, and subsequently models them through random variables. A brief introduction to joint distribution (modelling) through copula is also included in the course for the modelling of joint distribution. The course also covers the joint and conditional distribution of events, which eventually leads to formulating probabilistic solutions for existing challenges across the domain. Furthermore, an introduction to machine learning models and their working principles will help in understanding the suitability of data-driven models and assessing their performance.
INTENDED AUDIENCE: Academician, students, Industrial Personnel
PREREQUISITES: Basic Knowledge of Probability and Statistics
INDUSTRY SUPPORT: Mathworks
