Definition Of Education

There is no agreement among teachers, psychologists, politicians, and philosophers as to the purpose of education, nor is there any agreement as to what constituents education. If the purpose is to train good citizens, we are faced with the fact that concepts of good citizens differ in different countries. Can be an attempt done by the adult members of a human society to shape the development of the coming generation in accordance with its own ideals of life. This seems an unsatisfactory definition because:

a – It is a definition of training rather than education, and
b – The rising generation will live in the world of to-morrow.

Whatever definition we accept of education and of the purpose of education, it will be colored by our own philosophy of life. There appears to be a need for each one of us to define our own ideals and purposes. We may then hope for the good fortune to be able to realize them in part.

The attainment by each child of his maximum potential intellectual efficiency through the cultivation of good mental habits would result in an increased measure of human happiness.There is nothing new in this, for many will see in this faith purely a variation of a Greek conception of happiness. This belief, held by a teacher, wave rise to a personal problem. What means can be discovered that will result in each child's attaining the maximum possible intellectual efficiency. The problem has been tackled in a restricted sphere, mainly since a group of children whose mental powers are so limited that only by exercising them at their maximum efficiency can they hope to attain any real happiness.

We have to draw attention to a view that the overriding aim of the teacher is the matching of capacity by attainment.

Education has been passed down from above, and hitherto attempted chiefly through the medium of words. We believe that it should be built up from below, and that for the majority it should be chiefly through the medium of the concrete, the visual, and the everyday.

The first requirement for all who teach, or who aspire to teach, appears to be an appreciation of:

a – The difference between education and instruction,
b – The different levels of ability among children,
c – The different types of ability among children.

There is a fundamental distinction between education and instruction; between the concept of the development of talents inborn and individual, and the conveying to a person of a body of information. The transition in schools from "chiefly instruction to chiefly education has been delayed by large classes, but it is taking place.

Teaching, as we understand it, should generally be not lecturing or talking by the teacher, but largely

a – Preparation before the lesson period of exercises that afford opportunities for activity by the pupil;
b – The stimulation of interest, ie the creation of the right emotional environment (in which, or course, oral teaching has some place). …

Programming Languages ​​of Data Science

Data Science is a study of analyzing data in different aspects. In several cases of consideration of data analysis, there is a general abstract framework that describes a basic structure on how data has to be designed. For example, in the generation of music notes, there's a certain criteria like using only particular music notes for the relevant tunes. Describing data analysis is a difficult conundrum. Developing a framework involves considering the elements of the data and implementing it using programming language.

Why should we use programming languages ​​for data analysis?

As we know, data is used in many streams such as banks-to store customer details, hospitals-to store patient records and so on. For this, we require a place to store all the data. To make it function according to the requirements, we make use of programming language.

Let's take a look at the different programming languages ​​that we use for Data Science.

Programming Languages-

  1. Python-the most widely used, popular language at present, used for a vast number of applications and also in data science. The major reason of using python is because of its powerful tools and user-friendliness. It is an interpreted language as it produces the output simultaneously as we provide input to the interpreter. So it provides a base for all the data to be stored.
  2. R- it is also a programming language that is specifically designed to meet the needs of data miners. The most basic IDE (integrated development environment) used is RStudio. It is a user-friendly programming that consist of built-in functions to make it easier to handle.
  3. Java-is the widely used and popular language used for various applications. It has many IDEs just like the other languages. Java can be linked with the databases very easily and that is the main reason we use it for many purposes.

There are many other languages ​​such as c / c ++, scala, perl, julia that are used for data analysis.

As there is a lot of scope for a career in data science, the knowledge of these languages ​​play a major role in building your career. Programming is a must in all fields these days. Especially when you are dealing with data. But having knowledge only in programming do not yield you much. To consider this, let's take a look at the general question that might arise.

Who should get to the field of data science?

The answer is obvious. If you have the skills that meet the requirements of a data scientist, you are good to go! Let's consider the skills that are required.

  1. Statistical skills: the reason this is important is because data deals with quantitative analysis of data.
  2. Programming: as mentioned earlier, programming is required to design the framework for holding data.
  3. Ability to work with unstructured data- many of the business organizations recover data in unstructured form. The data scientist must be capable of dealing with such kind of data.