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Augmented Analytics

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May 11, 2024 5 minute read

Augmented Analytics represents a fusion of data science and machine learning techniques with business intelligence tools. It takes traditional data analytics a step further by automating the process of data preparation, analysis, and insights generation through artificial intelligence (AI). This allows even non-technical users to access and analyze data more effectively and efficiently.

Why Learn Augmented Analytics?

There are numerous reasons why someone might want to learn about Augmented Analytics. Here are a few:

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Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Augmented Analytics.

Lifelong Machine Learning

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Provides a comprehensive overview of augmented analytics, including its benefits, challenges, and implementation strategies. It is an excellent resource for students and professionals who want to learn more about augmented analytics.

Lifelong Machine Learning, Second Edition...

Paperback

$$$

Python Data Science Handbook

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Fits a part of the larger topic of Augmented Analytics. Machine learning subset of augmented analytics that focuses on using algorithms to learn from data. This book provides a comprehensive overview of machine learning techniques, including their benefits, challenges, and use cases.

Python Data Science Handbook: Essential Tools for...

Paperback

$$$

Python Data Science Handbook: Essential Tools for...

Paperback

Python pour la Data Science - Les meilleures outils...

Paperback

$$$

Python Data Science Handbook

Kindle Edition

Relevant careers

Data Analyst

Machine Learning Engineer

Business Intelligence Analyst

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