Course in Data Science and AI for Business

The Advanced Training Course in Data Science and AI for Business, which is not a master, is offered by the Department of Business and Quantitative Studies of the University of Naples Parthenope. The programme covers machine learning, business intelligence, generative artificial intelligence, programming for business analytics and text mining, and also addresses AI ethics and business strategies. The use of data to support decisions is now central in businesses, and generative artificial intelligence has opened up new possibilities for analysis and automation. The course offers short, targeted training that combines analysis techniques with their application to the business context, without requiring a two-year pathway.

The course lasts four months, with 144 hours of lessons and 18 credits, in blended format: online and in person in Naples. The cost indicated is €1,500. The language is not declared and Italian is presumed. The start date is not stated and the page does not highlight internships. The blended format, with online lessons and in-person activities in Naples, may suit those who work. However, the page does not indicate how the 144 hours are divided between the two modes or how many in-person days there are. The 18 credits awarded indicate a substantial commitment, to be weighed against other commitments.

The aim is to train professionals able to analyse large amounts of data and develop predictive models to support business decisions. The career opportunities are data scientist, business analyst, AI consultant, business analyst, data analyst, business process analyst and data engineer. Since it is an advanced training course, it does not award a master's qualification and should be considered as professional updating. The page also mentions AI ethics, an increasingly relevant topic for companies. It is aimed at graduates in technical, economic or statistical disciplines who want to become data scientists, business analysts or consultants. Before applying it is advisable to compare this information with that published on the university's official website, which may be more up to date than the page. It is also advisable to contact the department's teaching office to clarify any doubts about attendance, lesson calendar, assessment methods and organisation of the final exam. Those who work should carefully assess the commitment required, in terms of weekly hours and attendance, to understand whether the programme is compatible with other professional or personal commitments. It may also be useful to ask whether information sessions or orientation days are held, in which lecturers present the course and answer candidates' questions.