Every course from every provider we track, with the same filters over all of them: level, length, price, certificate and who stands behind it.
111 courses for “Complete Time Series Analysis for Data Science”
2 hours
An hour and a half of forecasting in Python, for somebody who has not done it before.
2 hours
Two and a half hours on decision trees — how one is built, and how it is read.
New courses, a couple of emails a month. One click unsubscribes.
4 hours
Three and a half hours on clustering: k-means, hierarchical methods, and choosing between them.
10 hours
Ten hours of data mining: the techniques, the algorithms and what each is for.
12 hours
Eleven hours of statistics and probability for data science, from first principles.
19 hours
Nineteen hours across SQL, Tableau, Power BI, Python, Excel and pandas — the analyst toolset in one course.
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.
12 hours
Generative AI for Data Science
Twelve hours across the generative AI stack, from the models to what is built with them.
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 analysis from the beginning, for somebody with no background in it.
12 hours
Eleven hours on the big data stack, from what the term means to the tools that do the work.
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.
7 hours
Seven hours building neural networks in TensorFlow 2, for people who have not built one before.
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.
5 hours
Six hours of statistics for data science in one sitting, from descriptive measures through distributions to hypothesis testing.
