Скачать или смотреть Complete Statistics Course for Beginners | Data Science Tutorial | Sheryians AI School

Instructor in this video - Akarsh Vyas
Complete Statistics for Data Science in One Video (5 Hours!)
Master the most important statistics concepts required for Data Science, Machine Learning, and AI — all in one detailed, beginner-friendly crash course.

In this video, we cover everything from descriptive statistics, probability, inferential statistics, to hypothesis testing, distributions, confidence intervals, correlation & regression, and more — explained with examples, visuals, and real-world data science context.

GitHub link - https://github.com/AkarshVyas/youtube...
Notes - https://drive.google.com/file/d/1MZoD...

✅ Topics Covered:

What is Statistics?

Types of Data & Scales of Measurement

Measures of Central Tendency (Mean, Median, Mode)

Measures of Dispersion (Range, Variance, Standard Deviation, IQR)

Probability & Conditional Probability

Bayes' Theorem

Probability Distributions (Normal, Binomial, Poisson)

Hypothesis Testing (Z-test, T-test, Chi-square test, ANOVA)

Confidence Intervals

Correlation vs Causation

p-value and Statistical Significance

Statistical Thinking for Machine Learning
...and much more!

Whether you're a Data Science student, ML enthusiast, or preparing for interviews, this video has everything you need to understand statistics deeply.

No prior experience needed — ideal for absolute beginners!

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00:00 - 00:25 - Introduction
00:25 - 34:02 - Statistical Visualization
34:02 - 43:18 - Measure of Central Tendency
43:18 - 54:13 - Measure of Spread
54:13 - 01:01:29 - Outliers
01:01:29 - 01:06:59 - 5 number summary
01:06:59 - 01:14:15 - Outliers Code
01:14:15 - 01:26:00 - Variance and Standard Deviation
01:26:00 - 01:38:09 - Density Curve
01:38:09 - 01:54:44 - Z score
01:54:44 - 02:01:15 - Basic Probablity
02:01:15 - 02:09:59 - Probablity Events
02:09:59 - 02:20:55 - Addition Rule and Multiplication Rule
02:20:55 - 02:38:19 - Conditional Probablity
02:38:19 - 02:48:03 - Bayes Theorem
02:48:03 - 03:08:04 - Hypothesis testing Basics
03:08:04 - 03:31:35 - Z-test
03:31:35 - 03:40:53 - Z-Test Code Implementation
03:40:53 - 03:50:52 - T-Test
03:50:52 - 03:58:04 - T-Test Code Implementation
03:58:04 - 04:09:34 - Two Sample Test
04:09:34 - 04:14:57 - Two Sample Test Code
04:14:57 - 04:29:19 - Chi Square Test
04:29:19 - 04:38:07 - Chi Square Test Code
04:38:07 - 04:48:05 - Annova Test
04:48:05 - 04:55:42 - Covariance and Correlation
04:55:42 - 04:56:00 - Outro