How to ACTUALLY Learn the Math for Data Science

In this video, I am going to explain to you the ACTUAL maths you need to be a data scientist.

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TIMESTAMPS:
0:00 Intro
0:41 What To Learn
2:18 Probability & Statistics
6:11 Calculus
9:10 Linear Algebra

WHO AM I?
Hi, I'm Egor! I am a Data Scientist with a master's in Physics currently living in London. I share data science tutorials, advice and general tech topics!

💙 DISCLAIMERS & DISCLOSURES
This content is for educational and entertainment purposes only and should not be considered as professional advice. Views and opinions are my own and do not represent or reflect the opinions of my current or past employer or any organisations I am associated with.

This description contains affiliate links that allow you to find the items mentioned in this video and support the channel at no cost to you. Thank you for your support!

[ganaparthileela]

Also go and check maths for data science in Geeks of geeks, the syllabus description is in good structure.
1. Linear Algebra & Matrix:
Linear Combinations
Vectors & Matrices
Quantities
Vectors
Matrices
Transpose Matrix
Inverse Matrix
Trace of a Matrix
Determinant Matrix
Dot Product
Linear Mappings
Functions
Measurements
Linear Mapping Composition
Vector Spaces
Formal Rules
Algebraic structures
Vector subspaces of a Linear Mapping
Data Redundancy
Linear dependence
Basis and dimension
Dimension of matrix spaces
Fundamental Theorem of Linear Algebra
Data Information
Partition of linear mapping domain and codomain
Data Partitioning
Mappings as data
The Singular Value Decomposition (SVD)
2. Probability & Statistics:
Probability
Continuous and Discrete Random variable
Central Limit Theorem
Probability distributions – Binomial, Poisson, Normal
Statistics
Mean, Median and Mode
Standard Deviation and Variance
Similarity measures – Pearson, Cosine, Spearman
Hypothesis testing
T-test
Paired T-test
p-value
F-Test
z-test
3. Calculus:
Maxima and minima
Mean value theorem
Product and chain rule
Taylor’s series
Derivatives
Gradients of Matrices
Backpropagation
Gradient Descent Algorithm
Useful Identities for Gradient computation
Higher-Order Derivatives
Multivariate Taylor Series
Fourier Transformations
Area under the curve
you should also have some discrete math knowledge and that is listed below.
4. Geometry & Graph Knowledge
Deals with the angles, measurements, and proportions of ordinary objects
To understand Distribution plots, Scatter plots, Boxplot (quartile, percentile)
To visualize the graphs and ability to generate insights from them.
Convex and Concave graphs and their properties

[alexchan]

Your video series is a god sent for someone trying to break into data science, seriously, thank you 🙏🏼

[ChristopherCordero-upxq]

Do I need to learn the same math for data analytics?

[AliceShisori]

I'm actually a dropout and have mostly worked jobs with absolutely zero math included, I've been learning python and sql and while I'm digesting slowly thus far, do you think there's really a pathway to learn math from scratch for people like me? I most likely will never reach your level but I just need to reach the "bare minimum" for this field, or for any kind of analytics really.

Been spending much efforts to learn so I just don't wanna give up this soon. really appreciate the videos bro

[stevestead]

Great summary of the data science mathematics landscape. I have been a practicing data scientist for 6 years and have had to learn most of this stuff in a piece-meal, 'bottom-up' manner. It's great to have someone present the essential topics in a top-down 'helicopter' view - really useful to see where the different parts fit in to the overall picture. Thanks for putting this video together. There are scary numbers of data scientists in industry that just run the pre-canned statistics and machine learning packages in R and Python and who don't really understand the mathematics that underpins it all.!

[jsc]

This is great, thank you! Really clear explanations

[harrysdatajourney]

Really great video Egor. This is super helpful!

[MelissaB]

I have a master's in math, but looking for things I need to review. Did you really learn linear algebra in high school? That wasn't even first year of college for me.

[Jack-epyj]

Hi Egor, I am stuck in choosing a BSc. CS+Ai (which doesn't have any mathematic moules and is from the university that i like)(Aberystwyth Uni), and a BSc. Data Science (which has, of course, statistics and mathematical modules from Coventry Uni). Which should i rather choose? Should I choose Aberystwyth and learn mathematics and statistical from self-study?

[supahottfire]

Hi I really liked your video. However, I think that the Mathametics for Machine Leanring book is extremely complex. I come from an engineering background but trying to do data science now. Are there any other books you would recxomend as a one stop shop? Are the videos a one stop shop to learn that subject ? Any answer woild he helpful.