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Statistics for Data Science

Video Description

Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks

About This Video

  • No need to take a degree in statistics, just go through this course and get a strong statistics base for data science and real-world programs;
  • Implement statistics in data science tasks such as data cleaning, mining, and analysis step by step
  • Learn all about probability, statistics, numerical computations, and more with the help of R programs

In Detail

Do you wish to be a data scientist but don't know where to begin? Want to implement statistics for data science? Want to get acquainted with R programs? Want to learn about the logic involved in computing statistics? If so, then this is the course for you.

This course will take you through an entire statistics odyssey, from knowing very little to becoming comfortable with using various statistical methods with data science tasks. It starts off with simple statistics and then moves on to statistical methods that are used in data science algorithms. R programs for statistical computation are clearly explained along with the logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks.

By the end of the course, you will be comfortable with performing various statistical computations for data science programmatically.