Data Analytics and Natural Language Processing for Courses Curriculum Design

Nowadays, we have gaps between job market demands and competencies that students acquire during their university studies. Course curricula in many cases lack practical content that is relevant for employers. With advances in data analytics algorithms efficiency and with automatic data collection from online resources such as online job postings and surveys, we plan to utilize modelling, natural language processing and machine learning algorithms to extract useful information about relevant skills and qualifications from data, to find patterns and develop insights. We would use these data-driven research results to identify management competencies and technical skills for students to be included in courses curriculum. The aim of this project is to help universities to create or adapt master programs in data analytics that increase likelihood for students to find jobs after their graduation as graduating students would possess all necessary skills that are needed in the job market.

Faculty Supervisor:

Roy H Kwon;Oleksandr Romanko

Student:

Partner:

Kyiv School of Economics

Discipline:

Business

Sector:

Education

University:

University of Toronto

Program: