Over the past few years, things have changed a lot; in this 21st century, data is the fuel of various industries. And ever since Covid, the need for data has become essential to the world in this age of technology. For enterprises, the problem is understanding how to use that data, and in doing so, industries require a data scientist.
There aren’t sufficient needed individuals who have acquired the skill to interpret the data and make it into valuable insights. Hence, People with solid knowledge of data science are becoming more useful than ever.
What is Data Science?
The term ‘Data science‘ can be defined as a combination of mathematical models, business acumen, tools, algorithms, and machine-learning techniques. All of these are of significant importance in uncovering hidden insights or patterns from raw data. These insights and patterns can significantly influence the formation of industry-leading business decisions in future.
A data scientist is responsible for finding trends based on historical data that can be useful for current decisions and designing structures to forecast future developments.
Why learn Data Science?
We tend to think that what we are learning has any value in the future. You may consider these reasons:
- High Demand
Forthcoming job seekers have several opportunities. It is the fastest-growing job on LinkedIn, and the US Bureau of Labour Statistics is expected to create 11.5 million jobs by 2026. The field of Data Science is therefore highly employable.
- Versatility in nature
Data Science is a versatile field widely used in healthcare, banking, consultancy services, and e-commerce. Thus, providing you to have the opportunity to work in various areas.
- Highly Prestigious
Data Scientists allow companies to make smarter business decisions. Companies rely on Data Scientist’s expertise to deliver better results to their clients & giving Data Scientists a powerful stance in the company.
- Making Products Smarter
Data Science comprises the usage of Machine Learning which has facilitated industries to create better products for customer experiences.
For instance, the auto industry uses data to create autonomous, safe, and flexible vehicles. The idea is to build machines that think in terms of data.
The pace of adoption of machine learning by large enterprises is rapidly increasing due to the need for Data Scientists in various fields. Hence businesses are looking for more out of their data, whether in Finance, Retail, IT, or Banks.
Why prefer a Data Science Online Course?
- SELF-PACED LEARNING & FLEXIBILITY:
Taking advantage of the Great Learning’s data science courses, many learners could study at 11 pm like a night owl, or 4 am like an early bird when they want to. An online program provides you with all of the resources needed to complete your education at your pace.
- GREAT VALUE & AFFORDABILITY:
Traditional learning has become more costly, whereas E-Learning is much cheaper than the former. On the other hand, taking an online course would save you time, money, and travel expenses.
Moreover, one can study in hazardous conditions like heavy rain, storms, bodily damage, pandemics like Covid-19, or other adverse conditions.
- MORE EFFECTIVE
Taking a Data Science program through E-learning lets you learn from experts who specialize in particular areas in a shorter period. It is a faster way to learn since the experts cover specific topics in a shorter period.
Skills to enhance before enrolling in Data Science Program
- In-Depth understanding of R programming :
R programming is used for data analysis, as an environment for statistical analysis, data visualization
- Get in touch with Python coding:
Since Python has a rich set of libraries/packages for building and deploying mathematical models, it is frequently used to implement mathematical models.
- Knowing MS Excel:
Microsoft Excel is indispensable in data entry jobs as a convenient means to calculate formulas, create equations, and create diagrams out of a messy collection of data.
- SQL database/coding:
Some hands-on experience with SQL database/coding is required. The software is used mainly for preparing and extracting data. As well as analyzing graphs and networks, it can also uncover fraudulent activities.
Available Job roles
- Business Analytics Professional:
Business analytics professionals use the data to generate insights into the business. To become a data-focused business analytics professional, you need the technical data management and manipulation skills.
- Data Scientist:
Data Scientists construct data models and simulations in a Big Data environment. Specialized in mathematics and statistics, these data scientists are also intrigued by building and deploying machine learning models.
- HR Analytics Professionals:
HR analytics professionals are responsible for looking into ways to reduce attrition rates, find out the most effective recruitment channels, and solve horrendous problems related to HR functions.
- Big Data Analysts:
The Big Data Analyst is responsible for ensuring that services are implemented smoothly and that Big Data processes are carried out by working with data scientists and data architects.
- Business Intelligence Professional:
BI professionals analyze past trends with the help of tools such as Tableau, Power BI, etc., to develop and implement business strategies. They also track all performance metrics and provide insight into each department.
Additionally, ML Scientists, AI Analysts, AI Engineers, AI/ML Developers, Associate Data Scientists, Deep Learning Engineers, Decision Scientists, Data Visualization Specialists, and others may be available.
Current Situation Of Data Science In India
According to AIM Research, in India, there were 137,870 jobs in data science in June 2021 and witnessed a 47.1 percent increase in open jobs requirements as compared to June 2020
India contributed to 9.4 percent of the total global analytics job openings, rising from 7.2 percent in January 2020.
The market for data science is slated to grow from $37.9 billion in 2019 to $230.80 billion by 2026, according to LinkedIn’s Emerging Jobs Report. Since 2012, the data science sector has experienced a 650 percent growth rate.
Conclusion:
This field is growing year by year; in the summarized form, we can understand that data science is about applying mathematical models and other tools to help businesses make good decisions.
To be a Data Scientist, one needs good knowledge and understanding of Statistics, Tools, and Business to get the best data science certification online from Great Learning. As far as prerequisites go, you should have some programming experience, and you need a good grasp of Algebra. Knowledge of Linear Algebra and Calculus is not required, but it is highly advantageous.
