DATA SCIENCE: THE STUDY OF DATA ABOUT DATA

In today’s world, everything is automated. From the morning alarm, coffee maker, vehicles you find on roads, Xerox, scanners, washing machine, dishwashers, fridge, mobiles, laptops, television sets, radio, tablets to iPad, and much more. All of this in general is called a machine. The growing technology has increased the importance of using machines. Building machines involves programming it according to user needs and that introduces several coding jobs. The machines that we use have certain storage to store the data it receives and the data that has to be sent. The programmer must code in such a way that the data is able to flow back and forth. For this to happen, the machine should be able to understand the command of the user. There might be many purposes of each user. Not everything can be programmed to handle such huge data and to be able to understand different requests of operations. This introduces the concept of machine learning. Machine Learning is the ability of a machine to understand the command the user gives and to work accordingly. Machine learning is achieved using the concept of Artificial Intelligence, the intelligence that the machine has. Data Science uses machine learning for data analysis. Data science help AI to figure out the future use of data and make it happen. It uses machine learning, language processing and computer vision.

Various fields used in the artificial intelligence are as follows:

·         Problem solving and reasoning.

·         Knowledge representation.

·         Creativity

·         General intelligence

·         Learning

·         Planning

·         Natural language processing

·         Perception

Three types of machine learning based on consideration of algorithms:

·         Supervised Machine Learning Algorithms: to predict the patterns of data and deals with labels.

·         Unsupervised Machine Learning Algorithms: does not deal with labels. They arrange data into clusters.

·         Reinforcement Machine Learning Algorithms: it is used as a switch to a particular condition to choose an action.

Requirements for Artificial Intelligence in the field of data science-

·         Analyst: as mentioned earlier, when you have to deal with large volumes of data, it is highly important to consider a few parameters like structure of data, location of processed and raw data to be stored. It is his/her responsibility to fix it in case of errors.

·         Statistician: you should have the ability to conclude on the available information about its processing.

·         Data Scientist: the person who analyses, interprets and is responsible for data on the whole. Current data jobs are in demand of data scientists and if you are an able data scientist, that adds up to your resume!

·          Researcher: staying updated on the present needs and the technology is very important. At the same time, being aware of what has to be done is equally important. So, a researcher is the one who finds out the present trends of the technology.

Skill sets required for data science to develop Artificial Intelligence:

·         Programming skills

·         Software development

·         Logical thinking and reasoning.

·         Analyst

·         Technical

·         Statistics

·         Data modeling and evaluation

·         Distributed computing

·         Knowledge of database

·         Robotics

·         Physics engineering

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The scope of data science in various fields is enormously increasing day by day, data has become the most important field in the present world. If you build a career in a versatile field like this, you can lead the world. For this purpose, Excelr introduces you to data science course, Singapore that trains and helps the future risers of the world into the world of data to bring out the best use of technology.