Course 2 : Statistics Essentials – Primer
Course Curriculum
Essential stats for DS
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Essential stats for DS : why stats and maths – overview
19:20 -
MCQ : statistics overview
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Data Types, Tables, and Feature Types Explored
16:20 -
MCQs : Data tables & feature types
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Exploring Simple and Advanced Sampling Strategies: with Python Demos
40:30 -
Central Measures in Data: From Basics to Winsorizing
23:26 -
Exploring Data Dispersion Measures
36:02 -
Data Distributions: A Comprehensive Guide, with hands on python code
01:01:23 -
Exercise : Calculate PDF of a score (dummy data)
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Exploring Statistical Measures: Kurtosis, Skewness, and Symmetry
16:00 -
Covariances in feature engineering (data science/ machine learning
13:48 -
Correlations and Multi-collinearity in Feature Engineering
20:30 -
Exploring Correlation Measures in Data Science
15:14 -
quick test on PDF/CDF
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Quick test on PDF/CDF
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