With more than 6 billion connected devices active over the internet, tech jobs and related skills have taken centre stage. Out of all, data science became the buzzword of the tech world and an interesting career alternative for budding tech enthusiasts. Cited as “the sexiest job of the 21st Century” by Harvard Business Review, the job of a data scientist majorly revolves around collecting and processing data that adds value to businesses.
What is Data Science?
With more than 6 billion connected devices active over the internet, tech jobs and related skills have taken centre stage. Out of all, data science became the buzzword of the tech world and an interesting career alternative for budding tech enthusiasts. Cited as “the sexiest job of the 21st Century” by Harvard Business Review, the job of a data scientist majorly revolves around collecting and processing data that adds value to businesses.
By definition, data science is a study program that deals with volumes of data using modern tools and techniques to find unseen patterns in data, hidden information to make decisions. To build predictive models, it uses complex machine learning algorithms and enables better decision-making. The study of data lets you-
- Find the leading cause of the problem,
- Perform the exploratory analysis,
- Model out the data with the help of algorithms,
- Communicate and visualise the results extracted from the data.
Prerequisites of Data Science
Here are some of the technical concepts that you should know before taking up a data science program:
- Machine learning
It is the backbone of data science, and every data scientist needs to have a good grasp of machine learning and basic knowledge of statistics.
- Modeling
Modeling is also a part of machine learning that involves identifying the algorithm to find out the solution to a problem.
- Statistics
It is the core of data science that helps you extract more meaningful results.
- Programming
Some level of programming like python, R.python is required to execute a successful data science project.
- Databases
Scientists interested in data need to understand how databases work and how to manage them and extract results.
Lifecycle of a Data Science Project
The stages involved in the life cycle of data science project includes:
- Concept Study
The first step in the life cycle of data science is studying the concept. It involves understanding the problem by performing a study of the database.
- Data Preparation
Data preparation is the most crucial step of a data science project since raw data cannot be used. Data scientists must examine the data to understand the gaps by following some steps like Data Integration, Transformation, Reduction, and Cleaning.
- Model Planning
After the data is cleaned up, the next step is to choose a suitable model that must match the nature of the problem. Tools that are crucial for model planning are R, Python, Matlab, and SAS.
- Model Building
Using the analytical tools and techniques, you can manipulate the data and build up the model.
- Communication
A good scientist should have the ability to communicate their findings to business-minded people.
- Operationalize
Once the findings get approved, they are initiated.
Data Science as a Career
Data Science is applicable in many industries, including healthcare, gaming, logistics, fraud detection, etc. To build up a career as a data scientist, it is essential to consider a full-time data science program to understand the subject matter. Over the last five years, the job vacancies of data scientists have snowballed. Some of the critical job roles that an applicant with a data science degree can apply for are:
- Data Scientist
The work of data scientists is to analyze large amounts of complex and raw information to find the patterns that can help an organization form their business strategies. It is one of the most sought after job profiles at the moment. Industries are on the hunt for qualified data scientists that can make sense of their data and help boost their business.
- Machine Learning Engineer
Machine learning engineers need strong programming and statistics skills along with theoretical knowledge. In addition, these engineers are responsible for running tests and experiments to check the performance and functionality of an organization.
- Machine Learning Scientist
These scientists are responsible for researching new data approaches and algorithms.
- Data Architect
Data architects ensure that the data solutions are built for performance and design analytics applications.
Other than these, the data science field offers different career options as well, including Data engineers, Statisticians, Data consultants etc.
Data science experts are needed in almost every sector of the economy. Millions of businesses and governments rely on considerable data to offer the best possible services. If you want to set your career in data science, you must join a reputed institute that offers the best data science program. We know that as we are beginning to carry our business online, we tend to share data with organizations. No matter how much data is accumulated by brands, it will be of no use if it is not processed. For this, they need a data scientist. Data science allows you to process and refine unorganized data to deduce patterns and make future predictions. This way, organisations can help modify their marketing strategies and cater to their customers better.
The demand for data science professionals is increasing day by day. Due to this increasing demand, various institutes are providing data science online programs to aspiring students. Hero Vired offers different programs, some for working professionals while others for young professionals who are looking for more intensive full-time experience. They offer integrated and postgraduate diploma in data science. Upon completing the programs, candidates receive certification from Hero Vired, a MicroMaster certificate from MIT open learning, and a postgraduate certificate from BML Munjal University. If you are interested in Data Science, do consider the Hero Vired reputed programs!
