Python for Data Analysis Full Course
5 hours
Five hours on analysing data in Python, from loading a file to a finished chart.
Every course from every provider we track, with the same filters over all of them: level, length, price, certificate and who stands behind it.
269 courses for “Statistics for Data Science: Probability and Statistics Tutorial”
5 hours
Five hours on analysing data in Python, from loading a file to a finished chart.
4 hours
Four hours of data analysis in Python: NumPy, pandas, Matplotlib and Seaborn.
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9 hours
Nine hours of React, taught step by step.
10 hours
Generative AI for Data Science
Nine and a half hours explaining generative AI for somebody starting from nothing.
23 hours
Generative AI for Data Science
Twenty-two hours on generative AI — the longest of these, and the most thorough.
2 hours
Two hours of R, taught as what it is: a language built for statistics.
2 hours
Two and a quarter hours of R for beginners, taught in Hindi.
5 hours
Five hours of SQL for analytics in one sitting.
3 hours
Eleven lessons on MySQL, from the first SELECT to the joins and aggregates an analyst uses daily.
10 hours
Ten hours of business analytics, from the statistics through to the dashboards.
24 hours
Twenty-four hours of business analytics: the statistics, the tools and the reporting.
12 hours
Eleven hours on the big data stack, from what the term means to the tools that do the work.
1 hour
A live session working one real dataset end to end, from first look to engineered features.
2 hours
Exploratory Data Analysis (EDA)
Two and a quarter hours of exploratory data analysis in Python, taught in Hindi.
3 hours
Exploratory Data Analysis (EDA)
Three hours on looking at a dataset properly before modelling it, and on the features built from what you find.
4 hours
Three and a half hours of OpenCV in Python, from reading an image to detecting faces.
9 hours
Eight and a half hours on deep learning, from neural networks to the frameworks that train them.
1 hour
An hour on descriptive statistics: the measures that summarise a dataset before any model touches it.
7 hours
A seven-hour tutorial on probability and statistics for data science, from a Stanford PhD.
7 hours
Twenty-seven lessons on statistics for data analysis and data science, taught in Hindi.