Information Technology encompasses how data is stored efficiently, categorized into information, retrieved and finally interpreted. The entire cycle of information processing delves into how data can be utilized to solve real life problems such as weather predictions, stock analytics, gene mapping, and many more. With the proliferation of digital devices of all shapes and sizes, data generation has multiplied enormously thus posing a critical challenge to how we store and interpret it. To make things more complex, most devices are now connected to the Internet thus generating as well as transferring huge amount of data between devices. In order to deal with this situation, machine learning and data science are being used to decipher and analyze large number of datasets that includes sounds, images, and videos besides text.

As the world moves towards total digitization and computers become an integral part of our lives, computing devices are ubiquitous. We at SAS aim to leverage computing to solve all kinds of social and environmental challenges.

Students will be able to assimilate and utilize their IT skills in diverse domains such as sociology, biology, economics, environmental science, to name a few. One important area where diverse domains intersect is simulating human activities, both mental and physical. The results of these simulations are visible in the form of intelligent robots, customized tailor-made medicines, self-driving cars, unmanned drones, and many others.

At SAS, students will have an opportunity to study the fundamentals of information sciences starting with computer logic and then gradually enhancing their skills in areas such as database systems, big data and machine learning. These skills will be in greater demand in the future in domains as wide as media and arts, neuroscience and genetics.

In addition to skills that are usually developed in IT programs, SAS program in Information Technology and Digital Society also aims to nurture students’ logical and analytical thinking, develop their team work skills and connect IT-specific competences with other disciplines. This will make SAS IT graduates more competitive in multiple jobs that will evolve in future in such areas as bioinformatics, sociology, economics, etc. The more traditional career options are:

  • Data analyst
  • Machine learning specialist
  • Database developer
  • Software programmer
  • Software consultant
  • Security analyst
  • Computer science researcher

Mandatory Courses:

  • Discrete mathematics: logic, set theory, combinatorics, graph theory
  • Programming languages: C/C++, Python
  • Data structures: lists, stacks, queues, trees, heaps etc.
  • Analysis and design of algorithms: computational complexity (Big O notation), searching and sorting algorithms
  • Database management systems
  • Machine learning and big data
  • Information security
  • IT project management