Data Science

Data Science

Introduction

The global data science platform market size was valued at USD 3.93 billion in 2019 and is expected to expand at a compound annual growth rate (CAGR) of 26.9% from 2020 to 2027. With rising investment in research and development, technological advances are occurring rapidly. As the enterprises are growing, the demand for technologies that can increase their productivity and efficiency is rising. Advancements such as Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) are all over the place which is driving the adoption of software and platforms. With data increasing every day, advanced data handling tools and platforms are contributing substantially to business growth.

The data science platform is one such software technology that is being widely used by industries today. This software that comprises of a variety of technologies for various advanced analytics and machine learning. It empowers data scientists to design techniques, reveal insights from information, and impart those experiences all through a venture inside a solitary situation. The projects carried out in data science comprise various tools designed at each step of the data modelling process.

The adoption of data science platforms is increasing rapidly today. The software provides high flexibility to open-source tools and scalability of computer resources. It can also be easily aligned with various data architecture. Apart from this, the platform enables version control, which empowers the data science group to team up on ventures without losing the work that has just been finished. Such benefits are substantially contributing to market growth.

What is Data Science?

Data Science has become the most demanding job of the 21st century. Every organization is looking for candidates with knowledge of data science. In this tutorial, we are giving an introduction to data science, with data science Job roles, tools for data science, components of data science, application, etc.

Data science is a broad field that refers to the collective processes, theories, concepts, tools and technologies that enable the review, analysis and extraction of valuable knowledge and information from raw data. It is geared toward helping individuals and organizations make better decisions from stored, consumed and managed data.

Objective of this Training

The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and draw insights from the data. From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly.

Then, he has the responsibility of making predictions from the data. The goal of a Data Scientist is to derive conclusions from the data. Through these conclusions, he is able to assist companies in making smarter business decisions.

We will divide this blog in various sections to understand the role of a Data Scientist in more detail.

Learning Objectives

By the ending of this Training, you will be able to:

 Apply quantitative modeling and data analysis techniques to the solution of real world business problems, communicate findings, and effectively present results using data visualization techniques.

 Recognize and analyze ethical issues in business related to intellectual property, data security, integrity, and privacy.

 Apply ethical practices in everyday business activities and make well- reasoned ethical business and data management decisions.

 Demonstrate knowledge of statistical data analysis techniques utilized in business decision making.

 Apply principles of Data Science to the analysis of business problems.

 Use data mining software to solve real-world problems.

 Employ cutting edge tools and technologies to analyze Big Data.

 Apply algorithms to build machine intelligence.

 Demonstrate use of team work, leadership skills, decision making and organization theory.

Eligibility Required

 BE/BTech. (All Streams)

 BCA, BSc (CS/IT) Degree

 PGDCA, MCA, ME /MTech

On completion of this training, you will be work as -

 Data Scientist

 Data Science Consultants

 Data Analyst

 Application Data Engineer

 Principal Data Analyst

 Product Data Scientist