Academic Programs

BSc in Management

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Data Science Track

The Data Science Track will be launched in April 2022 for students aiming to acquire the problem-solving skills for companies seeking innovative solutions. We will train data scientists who have the ability to utilize IT in corporate management and business by learning specialized skills in the IT field and business administration in parallel under the guidance of a fulfilling IT environment and practitioner teachers.

What is data science?

The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Nowadays, Facebook can automatically tag you in pictures, Netflix can recommend you videos, and banks can identify which customers are most likely to leave for a competitor.


Data science can be defined as a blend of mathematics, business acumen, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.

In data science, one deals with both structured and unstructured data. The algorithms also involve predictive analytics in them. Thus, data science is all about the present and future. That is, finding out the trends based on historical data which can be useful for present decisions and finding patterns which can be modelled and can be used for predictions to see what things may look like in the future.



Why study Data Science?


Industries need data to improve their performance, make their business grow and provide better products to their customers. Data scientists know how to use their skills in math, statistics, programming, and other related subjects to organize large data sets. Then, they apply their knowledge to uncover solutions hidden in the data to take on business challenges and goals.

Potential future career paths

  • Data Scientist
  • Data Engineer
  • Data Architect
  • Big Data Engineer
  • Business Analytics Specialist
  • Data Visualization Developer
  • Business Intelligence (BI) Engineer
  • BI Solutions Architect
  • BI Specialist
  • Analytics Manager
  • Statistician