Data Science – Understanding it and getting started

3 years ago

What is data science?

Data is considered the new oil. It is the most valuable and precious asset at present. The big giants like google are totally based on data they obtain. There is a popular saying like “your intelligence is only as strong as the data that backs it”, this explains the importance of the data in human life. The major problem in the modern world is finding insights into data. Data abundance is making it difficult for organizations to get the right insights of data. Data science plays an important role to deal with unstructured raw data gathered by various sources. Data science is the study of a combination of mathematics, statistics, programming, and capturing data in ingenious ways, One of the major purposes of Data Science is to derive hidden patterns & trends from the data. This data can be used by businesses to enrich their customer’s needs.

Application of data science

        Data Science has been proved successful in creating a vast impact in nearly every major field. It has transformed the working of innumerable sectors & still on its way to explore the remaining untapped areas. Some of the core sectors include:

  1. Finance

Financial institutions have used data science to predict future values, automating financial tasks etc. Thus enhancing their user needs.

  1. Healthcare

Data Science plays a significant role in the healthcare sector. Data science has created wonders in this sector. It has helped in early detection and prognosis of diseases, helped monitor patient’s health.

  1. E-commerce

Data Science has transformed the E-commerce industries in a variety of ways. It has helped industries to showcase perfect items to their customers by studying their search patterns and thus maximizing their profits.

Careers in data science

        Data driven decision making is increasing in popularity. This is driving and creating various interesting and high paying jobs. These jobs include various profiles , demanding various different skills each.

1.  Data Scientist

Data scientists apply statistics, machine learning and analytic approaches to solve critical business problems. Their basic key function is to turn volumes of big data into valuable and actionable insights.

2.  Data Analyst

Data Analysts are experienced data professionals who can query and process data, provide reports, summarize and visualize data. They need to have some core skill like statistics, data visualization, exploratory data analysis etc.

3.  Data Engineer

They are software engineers who design, build, integrate data from various resources, and manage big data. They focus more on focus more on the design and architecture.


Best courses to learn data science

Here are some best sources to learn data science from:

1.  Youtube : This is the most easily and freely available source. There are many youtube channels to learn data science from. Some popular channels are Krish Naik, freeCodeCamp.org, Sentdex, Corey Schafer etc.

2.  Coursera : Data Science specialization by John Hopkins University is the best course on coursera.

Link : https://www.coursera.org/specializations/jhu-data-science

3.    Udemy : Machine Learning A-Z : Hands on python and R in Data science. Interested in the field of Machine Learning? Then this course is for you!

Link: https://www.udemy.com/course/machinelearning/


Future of Data science

        Data science is the most booming industry. The continuously increasing amount data is in fact fuelling data science, and helps in optimising the current models, algorithms and processes. Being an inter-disciplinary field it will impact a large amount of sectors. With tremendous amount learning resources available, it provides wondrous opportunities to nearly anyone, willing to learn data science. Data is like a non degrading resource which will last longer then the systems themselves. So, certainly one is assured that there will definitely be no decline in the data science industry and that it will always continue to provide promising careers.