A lesson at a time rather than one long session: each video takes one idea and finishes it.
The series opens with how to teach yourself statistics, then works through populations and samples, the measures of spread, distributions, the central limit theorem, p values, confidence intervals and the common tests.
It closes on the questions a statistics interview for a data science role actually asks.
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1 lesson, 8 minutes
An eight-minute introduction to machine learning: how a model learns from data, the difference between supervised and unsupervised learning, and where each is used.
5 hours
Six hours of statistics for data science in one sitting, from descriptive measures through distributions to hypothesis testing.
7 hours
A seven-hour tutorial on probability and statistics for data science, from a Stanford PhD.
1 hour
An hour on descriptive statistics: the measures that summarise a dataset before any model touches it.
12 hours
Eleven hours of statistics and probability for data science, from first principles.
13 minutes
What machine learning is, explained without the mathematics, in thirteen minutes.
1 lesson, about 50 hours
A single session on data science, about 50 hours, published on YouTube by Simplilearn. Watched here on the course page.
1 lesson, about 9 hours
A single session on data science, about 9 hours, published on YouTube by Intellipaat. Watched here on the course page.
1 lesson, about 6 hours
A single session on data science, about 6 hours, published on YouTube by freeCodeCamp.org. Watched here on the course page.
