🔥R For Data Science Full Course | Data Science With R Programming | R Full Course | Simplilearn

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This video by simplilearn is based on R for Data Science Full Course, we’ll start by learning data science from an animated video. This video is curated in collaboration with Real-time industry experts ensuring the data science aspirants have a well-versed understanding of data science with R. You will then learn the essential concepts in data science and understand the important packages in R for data science. You will look at some of the widely used data science algorithms, such as Linear regression, logistic regression, decision trees, and random forest, including time-series analysis. Finally, you will get an idea about a data scientist’s salary structure, Skills, Jobs, and resume.

Dataset Link – https://drive.google.com/drive/folders/1Wn2TRSbM2CHzxEk-qclzGJcyZT4LHeRV

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Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientists first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data, you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.

You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:

1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming, such as data types, tuples, lists, dicts, basic operators, and functions
3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions
Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave
4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package

Learn more at: https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training?utm_campaign=RForDSFullCourse6Sep22&utm_medium=Description&utm_source=youtube

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