ML - Text input data

I'm trying to explore an use-case in ML but stuck at a point. May i please request your advise please.

Have a service desk web application for logging tickets, which is essentially a form having various fields like -

subject, content, username, emailid, category - {hardware, application, datafix, mobileapp, etc.}, service group - {AAA, BBB, CCC, DDD, etc.}, domain - {email, walkin, phonecall, etc.}, priority - {high, medium, low} 

(Apologies for the poor quality of sample data provided above.)

Based on this info, the ticket is then manually assigned to respective team owners for resolution.

My intent is to use ML - based on the above fields, predict the Team who will work on this ticket. (Team ex. HR or IT or Desktop support or Pantry or Facilities, etc. )

1) Can this use-case be categorised as Multi-class classification problem? 2) The field values are stored as words in database. How can it be fed to my ML as numbers?

Please advise.

Thanks in advance, RB (on Python 3.6)