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Essential types of data analysis methods and processes for business success

Data Science Dojo

Exploratory analysis Exploratory analysis involves consulting various data sets to see how certain variables may be related, or how certain patterns may be driving others. Diagnostic analytics includes methods such as hypothesis testing, determining a correlations v/s causation, and diagnostic regression analysis.

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Why and How can you do a Masters in Data Science in India?

Pickl AI

Key subjects often encompass: Statistics and Probability: Students learn statistical techniques for Data Analysis, including hypothesis testing and regression analysis, which are crucial for making data-driven decisions. They use databases and Data Visualisation tools to present data clearly and concisely.

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Understanding the Synergy Between Artificial Intelligence & Data Science

Pickl AI

Synergy Between Artificial Intelligence and Data Science AI and Data Science complement each other through their unique but interconnected roles in data processing and analysis. Deep Learning: Advanced neural networks drive Deep Learning , allowing AI to process vast amounts of data and recognise complex patterns.

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.