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How to become a data scientist

Dataconomy

It involves developing algorithms that can learn from and make predictions or decisions based on data. Familiarity with regression techniques, decision trees, clustering, neural networks, and other data-driven problem-solving methods is vital. This is where data visualization comes in.

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8 Best Programming Language for Data Science

Pickl AI

It is popular for its powerful data visualization and analysis capabilities. Hence, Data Scientists rely on R to perform complex statistical operations. With a wide array of packages like ggplot2 and dplyr, R allows for sophisticated data visualization and efficient data manipulation. Wrapping it up !!!

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Introduction to R Programming For Data Science

Pickl AI

The programming language can handle Big Data and perform effective data analysis and statistical modelling. Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. How is R Used in Data Science? Accordingly, Caret represents regression as well as classification training.

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Introduction to applied data science 101: Key concepts and methodologies 

Data Science Dojo

It leverages algorithms to parse data, learn from it, and make predictions or decisions without being explicitly programmed. From decision trees and neural networks to regression models and clustering algorithms, a variety of techniques come under the umbrella of machine learning.