Data Science

Data Science Introduction -: Before we start data science first it must be necessary to know about it. Data Science are made two words data and science. Study of data for scientific way called the data science. In other words we can say that data are store in any system. Data are store in unstructured format. Data scientist are store this data in well format.

data science

Data Science is a branch of computer science but it is different to computer field. For understanding the different we understand the this

Computer Science branch we create the program and algorithm for record and process data Although data science cover any type data analysis who used the computer or not used the computer.

Data science are related to the Mathematics field. It is the near of statics because in this data are collecting, organize, analysis and present here.

Learning Path Of Data Science

Before you will start learning the data science it is necessary to know what is the part of data science and how is using in real life and what programming languages are used in data science.

1-: What Is Data Science

2-: Data Science In Real Life

3-: Statistics Essential

4-: R programming For Data science

5-: Python Programming for data science

6-: Data science with Machine learning

7-: Tableau

Data Science In Real Life

Data science is a fastest growing sector in this century. Every one using data science. For example if we are searching a C Language Learning center on google then it show many option.But here add will show the only c programming language center then the right person see the ad and buy this product. There are many feature of data science

  1. What is data science
  2. What does a professional do
  3. What is the use of data science in business
  4. Use case of Data science
  5. Data science People

Statistics Essential

Statistics is the branch of science of assigning a probability to an event based on experiments. It is the application of quantitative principles to the collection, analysis, and presentation of numerical data.Ace the fundamentals of Data Science, statistics, and Machine Learning with this course.

It will enable you to define statistics and essential terms related to it, explain measures of central tendency and dispersion, and comprehend obliquity, correlation, regression, distribution. You will be able to make data-driven predictions through statistical inference. there are some part of statistics these are here..

  1. Introduction of statistics-: understand the fundamental of data.
  2. Type of Data -: Sample or population data.
  3. Fundamental of descriptive statistics
  4. Calculate the measures of central tendency, asymmetry, and variability

R Programming For Data Science

R is a programming language that provide free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. This language is widely used among statisticians and data miners for developing statistical software and data analysis.

An essential programming language for data analysis,R Programming is a fundamental key to becoming a successful Data Science professional.We will learn how to write R code,learn about R’s data structures, and create your own functions. After the completion of r programming course, We will be fully able to begin our first data analysis.

1-: First we will learn R programming language. In this language we will learn these topics

  1. R Basics -: In this we we Learn Introduction of r programming, Variable, Math etc.
  2. R structure -: Data Structure In R
  3. R programming Fundamental
  4. Data In R programming
  5. String And Dates in R -: Understand the string and Dates in R

2-: The Second step to a data scientist is learning R – the upcoming and most in-demand open source technology. R is an extremely powerful Data Science and analytics language which has a steep learning curve and a very vibrant community. This is why it is quickly becoming the technology of choice for organizations who are adopting the power of analytics for competitive advantage.