From India Today Education Desk: Credit for launching the first academic program in data science was given in 2007 to Land Grant State University in North Carolina, USA, which devised a master’s degree program in data analytics.
Since then, several universities around the world have started offering graduate and undergraduate programs in data science (and related areas such as data analytics, NLP, and ML).
In India, SP Jain was the first b-school to launch a postgraduate accredited program in Big Data Analytics program in 2015, followed by its first undergraduate program in Data Science in 2018, along with three other universities around the world. It has started.
Data science programs around the world are gaining ground in terms of student admissions, as they offer significantly higher salaries and easier access to the entry-level job market compared to the job performance of graduate students with computer science engineering degrees. has been a big hit.
Interestingly, data science is a very versatile career as it can be applied to a wide range of industries, from healthcare to finance to e-commerce to transportation and logistics.
With the rise of big data and increased availability of data sources, organizations are looking to leverage data to make better decisions. Data science provides tools and techniques for analyzing large amounts of data and extracting insights from it that can be used to make strategic decisions.
Data science has the potential to drive innovation and create new products and services. By analyzing data and uncovering patterns and insights, data scientists can identify new opportunities for growth and development. With the increased availability of open source tools and resources, data science has become more accessible to a wider audience. This has helped democratize data science and make it more inclusive.
Dr. Abhijit Dasgupta, Director of SP Jain School of Global Management and Bachelor of Science in Data Science, shared a list of career options for students in the field of AI and Data Science.
1. Data Scientist: Data scientists are responsible for analyzing and interpreting complex data to find patterns and insights that help organizations make better decisions. Programming, data analysis, and machine learning skills are required.
2. Machine Learning Engineer: Machine learning engineers design and implement machine learning algorithms and models to automate tasks and create predictive models. Requires strong programming skills and knowledge of statistics and mathematics.
3. Artificial intelligence researchers: AI researchers conduct research on artificial intelligence and develop new algorithms and models to solve complex problems. Must have a strong background in mathematics, computer science and machine learning.
4. Business Intelligence Analyst: Business intelligence analysts use data to help organizations make informed decisions. Analyze data to identify trends and patterns and create reports and visualizations to communicate insights to business leaders.
5. Data analyst: Data analysts collect, clean, and analyze data to identify trends and insights. Statistics, data visualization and programming skills are required.
6. Data Engineer: Big data engineers design and implement large-scale data processing systems using technologies such as Hadoop and Spark. Requires strong programming skills and knowledge of distributed computing.
7. Data Architect: Data architects design and maintain the architecture of data systems. Requires a deep understanding of data modeling and database design.
8. Data Mining Engineer: Data mining engineers develop and implement algorithms to discover patterns and insights in large datasets. Programming and machine learning skills required.
9. Data Visualization Developer: Data visualization developers create visualizations and dashboards to help organizations better understand their data. Skills in programming and data visualization tools are required.
10 Data Quality Analyst: Data quality analysts are responsible for ensuring the accuracy and completeness of data. Must be proficient in data management and quality control techniques.
Overall, the right candidates with high-quality coding skills, industry certifications, and strong academic backgrounds are offered opportunities around the world at salaries unheard of a few years ago.
