"At the end of this course, you will be able to:Describe the role of probability theory, optimization and linear algebra in the field of Artificial Intelligence.Define probability distributions such as binomial and normal and its applications in ML model development.Conduct hypothesis tests such as Z test and t-test and how it is used in ML Model development.Explain optimization and linear algebra concepts and their applications in ML and AI.Conduct hypothesis testing, optimization and linear algebra using Excel."
Overview
Syllabus
Week 1: Descriptive Statistics and Data VisualizationWeek 2: Probability TheoryWeek 3: Sampling and EstimationWeek 4: Confidence IntervalsWeek 5: Hypothesis TestingWeek 6: Analysis of VarianceWeek 7: Correlation AnalysisWeek 8: Applied Linear Algebra
Click here for Syllabus
Click here for Syllabus
Taught by
Dinesh Kumar