# Data Science: 5 Statistics & Math tools

1. MEAN / MEDIUM

2. PERCENTILE

3. SKEWNESS

4. STANDARD DEVIATION

5. PCA = Pricinpal Component Analysis

1. Probability & Statistics

2. Linear Algebra (Matrix, Eigenvectors, Eigenvalues)

3. Optimisation : eg. Gradient Descent, etc.

4. Discrete Math in Computing

(想看更多合你口味的内容，马上下载 今日头条)
http://app.toutiao.com/news_article/?utm_source=link

# Math High-Pay Career in Data Science

https://towardsdatascience.com/data-science-jobs-with-their-salaries-171acd3bf9be

Gone are the days where Math graduates were destined to low-pay teachers in the 1960s to 1990s.

Now Math career is the hottest high pay job in the 2 key engines of the “4th Industrial Revolution” , ie Mind Automation by Machine Learning (in Big Data) and its ‘Young Mother’ Artificial Intelligence.

The 3 top jobs (by order of pay) :

1. Data Scientist (US \$120K) :

Skills : Math (Stats, Linear Algebra, Calculus, Probability, & potentially Algebraic Topology / Homological Algebra) + A. I.

Mathematician PhD preferred.

2. Data Architect / Engineer (US \$100K)

Skill: Math + IT (especially in Big Data technologies).

3. Data Analyst / (US \$65K)

Skills : IT + Business + some Math (Stats).

# Tutorial on Sheaves in Data Analytics Background: What is Sheaf (束) ?

https://tomcircle.wordpress.com/2014/05/05/sheaf-sheaves/ Lecture 1

Lecture 2 Lecture 2: What is Topology ?

Lecture 3: What is Sheaf ? Terms : Stalks (茎) together = Sheaf (束 / 梱)

Lecture 4: Data Structure as Sheaf

Lecture 5: Categorification

Lecture 7 & 8: Cohomology, Noise, Persistence Cohomology

<span More… (Total 8 video lectures)

Tutorial on Sheaves in Data Analytics: http://www.youtube.com/playlist?list=PLSekr_gm4hWLvFtJX0WUueVO65uhvBPrA