Steve kindly reminded me to revisit the question of how we might integrate data as a part-time or full-time concentration. We have a bit of time on this, as everyone’s dance card for this fall is full. But it’s worth starting the discussion.
We have some truly excellent data folk here at Northeastern, and Christoph Riedl is representative of a new crop of top international talent. He’s also a nice guy and, as you can see below, excited by the prospect of having some sharp journos sitting in his classes.
From: Christoph Riedl <email@example.com>
Subject: Re: Happy Summer!
Date: June 12, 2014 at 2:57:47 PM EDT
To: “Howe, Jeffrey” <J.Howe@neu.edu>
Cc: “Offenhuber, Dietmar” <firstname.lastname@example.org>
Good to hear from you. Here are some thoughts – speaking purely from a subject matter perspective – I have no clue what hurdles there would be for a student to actually take those courses (i.e., cross college etc).
* I think all the 4 courses of the Data Science certificate would be great candidates. They are all 4 credit graduate level courses. Roughly, the courses are (1) computational stats I; (2) computational stats II; (3) data handling and data manipulation; (4) visualization (Dietmar’s course). Attached I’m sending you the course/program descriptions as it was used for senate approval. The first set of those courses is being offered in Spring 2015.
* I’ll be teaching a 1 credit mini course (yes, at the business school we have such things) on “Introduction to Business Analytics” this Fall. While this would not provide much actual “hands on” data analysis stuff, it could still be a good way to “get a sense of what can be done” and how this whole “big data” stuff gets applied in a business context. This mini course will run on two Saturday mornings in November.
* I’ll be teaching “Data Mining in Cyberspace” in Spring 2015 at CCIS which is an applied data mining class. That might be really interesting for your students. The goal there is to be very applied with lots of student projects and focus a little bit more on “doing things” rather than “theory and mathematics”. This course will be listed as a special interest course. I’d be exited to have one or two students from you program (or all 5 of them 😉 in my course. I envision to leave students a lot of freedom with regard to what they want to apply the machine learning to. So I’d be happy to “build” something to accommodate your students/their interests (e.g., say I’m teaching them something “clustering of text documents” then a student from the Information Assurance program could apply this to do email spam filtering while a student from the journalism program could apply it to look at partisanship in blog posts (just as a silly example)).
I hope this is helpful in any way. Happy to talk more.
On 2014-06-11, 6:51 PM, Howe, Jeffrey wrote:
I knew we’d be drawn together before long! I’m hoping you and Dietmar can advise me. I have my first five students entering our new Media Innovation Program, and I’m doing my level best to persuade one or two of them to specialize in data journalism. Ultimately I’m hoping to have a formal data journalism track created that uses that CSIS informatics certificate you two (among others, I understand) have done such admirable work on.
But this current crop isn’t necessarily sure if they want to use all their elective slots (we’re a 36-credit-hour program, and their journalism requirements and studios comprise 10 of those hours), and I’m trying to figure out what kind of options might exist for more of an a la carte approach.
Could you help guide me here? There seem to be wonderful offerings in both CCIS as well as ARTG within the IDV program (whew! acronyms!). If a student wanted to take two Web Dev courses and two Data courses for their electives, what might those look like? Or three data courses, perhaps?
I realize it’s probably a difficult, case-by-case question, but any help and guidance you can offer is hugely appreciated.