DataCamp is a platform that allows you to learn data skills at your own pace through a comprehensive learn-practice-apply-assess cycle. It offers nearly five hundred courses covering a wide range of topics, including data literacy, data engineering, artificial intelligence, data analysis, and visualisation. For instance, the course “Explainable AI in Python” guides you to build more transparent, trustworthy and accountable AI systems.
You can also practice the techniques you learn through real-world projects available on the platform. Additionally, you may participate in competitions to win prizes for donation to a charitable cause of your choice.
Certificates in data career, technology, and fundamentals are presented to validate your data skills. If you are interested in the insights and experience of data leaders and practitioners at the forefront of the data revolution, be sure to explore DataFramed, the weekly podcast.
Book Series on Springer: Springer Texts in Statistics
Statistics play a pivotal role in theories underlying data science. In addition to
Data Science: An Introduction to Statistics and Machine Learning,
Springer Texts in Statistics offers a collection of peer-reviewed advanced textbooks suitable for undergraduate and postgraduate students. Topics covered include, but are not limited to, statistical learning, categorical data analysis, regression, and Bayesian methods. They can be accessed through the
Springer Nature Link database page.
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