The inception of academic programs in Data Science dates back to 2007, credited to a land-grant state university in North Carolina, USA, which introduced the MS in Data Analytics program. Since then, numerous universities worldwide have followed suit, offering graduate and undergraduate programs in Data Science and related fields like Data Analytics, NLP, and ML.
SP Jain in India pioneered a graduate certificate program in Big-Data Analytics in 2015, later launching the first undergraduate program in Data Science in 2018, alongside three other global universities. These programs have witnessed significant enrollment due to their potential for better job prospects and higher salaries compared to traditional computer science engineering degrees.
Data Science presents a versatile career path with applications across various industries, including healthcare, finance, eCommerce, and transportation. With the exponential growth of big data and its availability, organizations are increasingly turning to data science to make informed decisions, driving innovation and creating new products and services.
Here are the top 10 career options in AI and Data Science, as shared by Dr. Abhijit Dasgupta, Director of Bachelor of Data Science at S P Jain School of Global Management:
1. Data Scientist: Analyzing complex data to uncover patterns and insights for informed decision-making. 2. Machine Learning Engineer: Designing and implementing machine learning algorithms to automate tasks and develop predictive models. 3. Artificial Intelligence Researcher: Conducting research and developing new algorithms to solve complex problems in AI. 4. Business Intelligence Analyst: Using data to identify trends and patterns and providing insights to business leaders. 5. Data Analyst: Collecting, cleaning, and analyzing data to extract meaningful insights. 6. Data Engineer: Designing and implementing large-scale data processing systems using technologies like Hadoop and Spark. 7. Data Architect: Designing and maintaining data systems architecture with a focus on data modeling and database design. 8. Data Mining Engineer: Developing and implementing algorithms to discover patterns and insights in large datasets. 9. Data Visualization Developer: Creating visualizations and dashboards to facilitate better understanding of data. 10. Data Quality Analyst: Ensuring the accuracy and completeness of data through quality control techniques.
Candidates with strong coding skills, industry certifications, and a solid research background are in high demand globally, with unprecedented salary opportunities compared to just a few years ago.
