Learn Data Science Tutorials 4+

Learn Data science guide, tutorials, FAQ's and many much more in a simple and easy way. Beginner to advance data science tutorials guide.

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Data Science
Data Science is the area of study which involves extracting insights from vast amounts of data using various scientific methods, algorithms, and processes. It helps you to discover hidden patterns from the raw data. The term Data Science has emerged because of the evolution of mathematical statistics, data analysis, and big data.

R programming
R is an open-source programming language that is widely used as a statistical software and data analysis tool. R generally comes with the Command-line interface. R is available across widely used platforms like Windows, Linux, and macOS.

- Are you a beginner? Gain the fundamental skills you need to speak the language of data with our data science app.

- Start with R programming and begin your data science journey with an in-demand and all-purpose technology. Learn 'R' and become a data science master. This learning path is great for both R programming beginners.

- Build up your data analyst skills with our SQL curriculum. In just 5 minutes a day, you’ll become an expert in relational databases and SQL joins, and will learn how to answer a wide variety of data science questions and prepare robust data sets for data analysis in PostgreSQL.

- Its time to master the basics of data science with R to get started on the path of exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

To learn R for data science we covered all aspects as follows:

• Introduction
• Data-Types in R
• Variables in R
• Operators in R
• Conditional Statements
• Loop statements
• Loop Control Statements
• R Script
• R Functions
• Custom Function
• Data Structures

Data science is the practice of mining large data sets of raw data, both structured and unstructured, to identify patterns and extract actionable insight from them. This is an interdisciplinary field, and the foundations of data science include statistics, inference, computer science, predictive analytics, machine learning algorithm development, and new technologies to gain insights from big data.

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