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Hands-on AI and data courses built around the datasets and models on the hub — plus the courses from other providers that people most often recommend.
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Google's entry-level data analytics programme: spreadsheets, SQL, Tableau and R, with a portfolio case study.
IBM's beginner programme in data science: Python, SQL, data analysis and visualisation, and machine learning.
Harvard's series on data science with R: basics, visualisation, probability, inference, wrangling, machine learning and a capstone.
A beginner-friendly course on querying data with SQL: filtering, sorting, joins, subqueries and data preparation.
Stanford's course on statistical thinking: descriptive statistics, probability, sampling, regression and hypothesis tests.
A short, free, hands-on course on pandas — the Python library for working with tables of data.
freeCodeCamp's free certification in data analysis with Python, NumPy, pandas, Matplotlib and Seaborn, earned through projects.
A free nine-week course on building data pipelines: containers, orchestration, data warehouses, analytics engineering and streaming.
MIT 6.0002: using computation to understand data — optimisation, simulation, statistics and an introduction to machine learning.
Microsoft's learning path for the Power BI Data Analyst Associate: preparing, modelling, visualising and analysing data.