The first academic program in Data Science was started by a state university in North Carolina, USA, in 2007. Since then, many universities worldwide have begun offering graduate and undergraduate programs in Data Science, along with related areas like Data Analytics, NLP, and ML.

Top 10 Career Options in AI and Data Science: Find Your Path to Success

In India, SP Jain was the first business school to introduce a graduate certificate program in Big-Data Analytics in 2015. They later launched the first undergraduate program in Data Science in 2018, along with three other universities around the world.

Data Science programs have gained immense popularity among students because they provide better access to entry-level job opportunities with higher salaries compared to computer science engineering degrees.

Data Science is a versatile career with applications in various industries, including healthcare, finance, eCommerce, and transportation & logistics.

As the amount of data keeps growing, organizations are utilizing it to make more informed decisions. Data science offers various tools and methods to examine vast quantities of data and extract valuable insights, which are beneficial for making strategic choices.

Data science jobs has the potential to fuel innovation and create new products and services. By examining data and uncovering patterns and insights, data scientists can discover new opportunities for growth and advancement. The availability of open-source tools and resources has made data science more accessible to a wider range of people, making it a field that includes everyone.

Dr. Abhijit Dasgupta, the Director of the Bachelor of Data Science program at S P Jain School of Global Management, has provided a list of career options in AI and Data Science for students.

High Paid Jobs of the top 10 AI and Data Science jobs

Data Scientist: A data scientist analyzes complex data to find patterns and insights that help organizations make better decisions. They need programming, data analysis, and machine learning skills.

Machine Learning Engineer: A machine learning engineer designs and implements algorithms and models to automate tasks or create predictive models. They require strong programming skills and knowledge of statistics and mathematics.

Artificial Intelligence Researcher: An AI researcher conducts research on artificial intelligence and develops new algorithms and models to solve complex problems. They need a strong background in mathematics, computer science, and machine learning.

Business Intelligence Analyst: A business intelligence analyst uses data to help organizations make informed decisions. They analyze data to identify trends and patterns and create reports and visualizations to communicate insights to business leaders.

Data Analyst: A data analyst collects, cleans, and analyzes data to identify trends and insights. They need skills in statistics, data visualization, and programming.

Data Engineer: A big data engineer designs and implements large-scale data processing systems using technologies like Hadoop and Spark. They need strong programming skills and knowledge of distributed computing.

Data Architect: A data architect designs and maintains the architecture of data systems. They require a deep understanding of data modeling and database design.

Data Mining Engineer: A data mining engineer develops and implements algorithms to discover patterns and insights in large datasets. They need programming and machine learning skills.

Data Visualization Developer: A data visualization developer creates visualizations and dashboards to help organizations better understand their data. They need programming and data visualization tools skills.

Data Quality Analyst: A data quality analyst ensures the accuracy and completeness of data. They need skills in data management and quality control techniques.

Overall, candidates with coding skills, industry certifications, and a research background will have opportunities worldwide at salaries that were previously unheard of a few years ago.