Data science combines maths and stats, programming skills and domain expertise. It deals with humongous volumes of structured and unstructured data and uses modern techniques and tools to generate meaningful insights. This is done by analysing, modeling, processing and then interpreting the results into actionable ideas. India has been experiencing explosive growth in the data analytics field due to the swift penetration of the internet, which doubled from 20% in 2018 to 41% in 2019 to an estimated 60% in 2022. The World Bank expects India to add more than 900 million users by 2025. So, almost all businesses feel the need for a data scientist.
This makes data science an extremely high-demand and promising career choice. It assures a good pay scale and attractive perks. Here is a detailed guide on data science prerequisites in case you wish to work as a data scientist.
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Skills required for a Data Scientist
You need to master both technical and non-technical data science skills. Here’s a look:
These are a few concepts that you will need to understand before becoming job-ready.
Machine Learning: An understanding of ML algorithms is a top requirement of the data science lifecycle. A lot of tasks can be automated with advanced ML techniques like time series, neural networks, reinforcement learning, natural language processing and outlier direction.
SQL: This is a data science prerequisite because it is needed to query and manage data present in a database. This is a domain-specific language that can be used for processing in a RDSMS (relational data stream management system).
Hadoop Platform: The main use of this is storing chunks of data when it exceeds the memory system. It is also used when the data needs to be distributed across multiple servers. Hadoop has high fault tolerance and scalability. It is a robust analytical platform that functions with Hive and Pig.
Statistics: It helps to capture and translate data patterns into actionable information. Having a good grasp of this subject is one of the top eligibility criteria for a data scientist. Scientists use statistics to gather, analyse, review and draw conclusions from data.
Programming: The most common languages are R Python and Python. They are fairly easy to learn and understand. The most popular languages are Julia, Java, Scala, C/C++ and Java Script.
To understand these, consider enrolling for GeekLurn’s Data Science Architect Program, which comes with 100% moneyback. It offers a detailed syllabus that covers the skills to make you job-ready. Also, it offers 100% placement at the end of the program. You can benefit from 6 months of live interactive classes, 18 months of sponsored project work, 1.5 years of real-time sponsored project experience and over 100 data science meetups, tech talks and webinars, all of which will position you better for your career.
The global big data market is projected to reach $122 billion in revenues by 2025. If you wish to tap into the lucrative career opportunity offered by data science, it’s a good idea to pursue a course to hone your skills. If you’re worried about data science course eligibility in India, don’t be. GeekLurn’s program is for students from both IT and non-IT backgrounds and for anyone who simply wishes to upskill.
Data science is more than just number crunching and professionals are required to be all-rounders to thrive in this exciting career. It is, therefore, necessary to hone a few soft skills like critical thinking, intellectual curiosity, effective communication, proactive problem solving and strong business sense. These do not require training or certifications but are an invaluable part of data science operations. Try to practise and develop them over the years to be able to stand out from the crowd and tick off the data science prerequisites for jobs.
Eligibility criteria for Data Science
Passing your class 12 or equivalent exam with PCM, Statistics or Computer Science subjects will stand you in good stead. The most common disciplines for data science eligibility in India include courses in Mathematics and Statistics (32%), Economics (21%), Computer Science (19%) and Engineering (16%). If you are a graduate in these disciplines, you can consider upskilling with knowledge of data science. This will help you tick off the eligibility for data science courses and increase your chances of being successful in the industry.
If you do not have a Master’s degree, don’t worry. You can complete a specialised course and meet the data science prerequisites to promote your career prospects.