End-to-End Data Pipeline with Snowflake and dbt
55 minutes
Building a working e-commerce data pipeline, start to finish, with Snowflake and dbt.
Every course from every provider we track, with the same filters over all of them: level, length, price, certificate and who stands behind it.
335 courses for “Excel Data Visualization Course – Guide to Charts & Dashboards”
55 minutes
Building a working e-commerce data pipeline, start to finish, with Snowflake and dbt.
3 hours
Nearly three hours on time series: the components, the models, and the forecasts built from them.
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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.
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.
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 on the business analyst role itself — the process, not only the tooling.
10 hours
Ten hours of business analysis from the beginning, for somebody with no background in it.