Every course from every provider we track, with the same filters over all of them: level, length, price, certificate and who stands behind it.
346 courses for “Cloud Computing Full Course in 11 Hours”
4 hours
Four and a half hours of Python from nothing, the course most people start with.
3 hours
Nearly three hours on time series: the components, the models, and the forecasts built from them.
New courses, a couple of emails a month. One click unsubscribes.
2 hours
Two and a half hours on decision trees — how one is built, and how it is read.
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 minutes
Natural Language Processing (NLP)
Twelve minutes on what natural language processing is and how it came to work.
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.
9 hours
Nine hours of React, taught step by step.
5 hours
Five hours of React for somebody who has never written any.
9 hours
Nine hours of React in one course, from the first component to a finished application.
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.
12 hours
Generative AI for Data Science
Twelve hours across the generative AI stack, from the models to what is built with them.
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.
10 hours
Ten hours of business analytics, from the statistics through to the dashboards.
