SAS education educational model majors course catalogue faculty

Deep Automation Module

Machine learning methods are foundational to the modern digital platforms and determine the processes of digital business transformation. The analysis of technolgical chains and the search for opportunities to implement adaptive automation systems is the core of this educational module. As part of the module students in-depth explore the following areas:

Natural Language Processing

Natural language recognition techniques are now widely used in products such as chatbots, voice assistants, and interactive consultation systems. Students master:

  • methods of building machine learning systems (classical methods and those based on neural networks)

  • specialized chapters of higher mathematics;

  • object-oriented programming in Python using modern open libraries for natural language processing.

Information Systems Architecture

The processes of digitalization and digital transformation require the application of complex technological solutions (digital platforms) based on distributed computing and data analysis processes. Students learn:

  • theory of information processes and systems (task decomposition and aggregation; application of simulation modeling for information system design; use of mass service systems);

  • distributed information systems (formalization of design and modernization tasks; analysis and selection of software and hardware implementation tools);

  • documentation of the information and management systems being designed (developing information models for systems using CASE-means).

This module also includes a Project Design Session (PDS) — a team-based intensive for rapid and comprehensive immersion of students in the field of in-depth automation. The PDS covers the following topics:

  • market analysis (trends, stakeholders, applications of digitalization);

  • the difference between digitalization and digital transformation as approaches to the tasks of developing companies;

  • modern technologies of digitalization and digital transformation processes;

  • positions in the labor market, responsible for the processes of digitalization and digital transformation. Formal and actual requirements to these positions.

During the module students are asked to form a hypothesis of digitalization or digital transformation of an budiness enterprise using methods of in-depth automation. To this end, we:

  • introduce students to the processes of an IT company;

  • immerse students in the activities of an IT company at the level of the most labor-intensive processes (where there is the greatest demand for digitalization);

  • keep a track of hypotheses for digitalization and/or digital transformation with the possibility of subsequent implementation.