We have designed this course to focus exclusively only on those concepts that are used in Machine Learning algorithms and implemented using Python. It serves as a prerequisite to effectively understand the larger picture to address real-time issues including concepts in Python and Machine Learning. This course covers concepts such as: sample, population, central tendencies, measures of dispersion, z score, min-max scaling,normal distribution, binomial distribution, central limit theorem,confidence interval etc