Maths and Statistics for Data Science: Fundamentals for Data Science

At the end of this course, you will know the fundamentals of maths and statistics for data science.

If you're brand new at data science, this is the course you want to build your foundational knowledge in math and statistics. I explain every concept like I would explain them to my 9-year old daughter: in simple terms, easily remembered, ingested and integrated.

The 1 hour 40 minute course is divided into 4 modules as followed:

Module 1: Probability - Random Variables - Expectation - Variance - Distribution - Law of Large Numbers - Central Limit Theorem. (16m29)

Module 2: Descriptive and Inferential Statistics (50m41)

• Part 1: Descriptive Statistics (measures of central tendency and of dispersion, distribution, shape of data) (00m33s)
• Part 2: Inferential Statistics (hypothesis testing and statistical significance, linear regression) (23m24)

Module 3: Vectors, Linear Transformations, Matrices, Matrix Algebra, Eigenvalues, Princpal Components Analysis (PCA) (23m08)

Module 4: Limits, Derivatives, Integrals, Optimizations, Gradient Descent, Area under the Curve, Linear Functions. (13m01)

So join me in this course of Math and Statistics Fundamentals for Data Science. Click the buy now button now.