Urban Planning/Public Policy/Data-Driven MPP Programs?

[Urban Plannerd]

I'm currently a data analyst in DC with the intention of grabbing an MPP and an MA if necessary to help pivot toward data-oriented urban planning. I'm interested in understanding the intersection between local communities and government policy, with an emphasis on infrastructure and planning. At the moment, I'm scouting out public policy programs, as I don't anticipate applying for a few years (graduated from Berkeley political science spring of 2016), and would love any advice or direction in terms of the styles of MPP programs. I'm looking for resources on the different "flavors" of the programs as well as any other advice one might have!

[PolicyStud]

I would recommend checking CMU's MSPPM program. You don't need to apply to the "data analytics" track specifically to take their classes.

I've written some pros/cons here:

 

Since CMU's MSPPM program is housed in the same college as the information science program, you'll have access to a wide range of data-related courses, from the more social science-oriented like econometrics to programming courses in machine learning. Courses at the School of Computer Science are available as well if you're up for them. When I was applying to other policy schools, I compared the curriculum with other programs, and I must say that the breadth and depth of CMU's courses in data science far exceeds that of any public policy program and even many data science programs. Most topics you might be interested in--from data warehousing to unstructured data mining and from visualizations to operations research--are available, and pretty much any other topic you can think of is covered in the computer science department.

If you have any questions, feel free to message me.

Edited July 1, 2017 by PolicyStud

[Urban Plannerd]

On 7/1/2017 at 6:43 AM, PolicyStud said:

I would recommend checking CMU's MSPPM program. You don't need to apply to the "data analytics" track specifically to take their classes.

I've written some pros/cons here:

 

Since CMU's MSPPM program is housed in the same college as the information science program, you'll have access to a wide range of data-related courses, from the more social science-oriented like econometrics to programming courses in machine learning. Courses at the School of Computer Science are available as well if you're up for them. When I was applying to other policy schools, I compared the curriculum with other programs, and I must say that the breadth and depth of CMU's courses in data science far exceeds that of any public policy program and even many data science programs. Most topics you might be interested in--from data warehousing to unstructured data mining and from visualizations to operations research--are available, and pretty much any other topic you can think of is covered in the computer science department.

If you have any questions, feel free to message me.

Thanks for answering! Will definitely look into CMU. What would you say are the specifications of most of the students and professors there? 

[PolicyStud]

20 hours ago, Urban Plannerd said:

What would you say are the specifications of most of the students and professors there? 

Could you clarify what you mean by 'specifications'?

If you're talking about people's background, I'll speak on my observations and experience.

• Students: I didn't come in with a coding background, but I'm walking out of my first year with knowledge on major database, machine learning/data mining, operations research, econometrics, and modeling concepts--stuff ranging from the traveling salesman's problem to predictive decision trees. I'm not going to be an operations research whiz with extensive knowledge of the most complicated methods like ARMA/ARIMA, but I am coming out with a broad foundation in the field. Some students (esp. in the data analytics and MISM-BIDA programs) came in with some knowledge on these subjects, but you definitely don't need an extensive coding background to perform well or learn a lot in the classes. I'd never done serious coding or math modeling before coming into the program. What's much more important is your capacity to learn and solve problems, and apply your technical knowledge to messy issues in social science.
• Professors:
  • Focus on methodology vs. subject-matter-expertise: There's a good mix of quantitative and non-quantitative professors. I'm not focused on urban policy, so I don't have extensive experience with professors in the field. Most of my friends in the field seem to find the coursework sufficient and complementary to their data analytics education. CMU-Heinz, and the university as a whole, certainly has an extensive network of economists and data scientists working on a variety of issues including racism in housing policy and police bias. 
  • Perspectives on data science: As I noted before, there's a variety of quantitative topics covered well here, so that's pretty great. But there's something else that's almost as important: a variety in how data science concepts are taught. I've found that professors teach machine learning here in a variety of different contexts, ranging from the conceptual to the programming/application-focused. Sometimes, the former is helpful to take a step back and familiarize ourselves with the breadth of the field. You'll find both here.
  • Difficulty: I don't think there's anything unique about this school's difficulty, so in brief, it depends. Like at any institution, you'll find that a few professors have a reputation for making students' lives hard, while a few others are relatively easy, and still others (the great majority of professors here) challenge us to grow.

Edited July 4, 2017 by PolicyStud

[MasterPublicPolicy]

I second the CMU recommendation. Definitely very data-driven. Probably the best you can find.

Another good recommendation is UC Berkeley Goldman. Not as explicitly data-focused as CMU, but still a quant-heavy curriculum.

[MasterPublicPolicy]

1 minute ago, MasterPublicPolicy said:

I second the CMU recommendation. Definitely very data-driven. Probably the best you can find.

Another good recommendation is UC Berkeley Goldman. Not as explicitly data-focused as CMU, but still a quant-heavy curriculum.

Also, since you did undergrad at Berkeley, you probably have a good chance of feeling out the program for yourself! Contact some professors and so on, and get a sense of the program's quant demands.

[Zuha]

Hi Everyone,

Its my first time posting here. I'm considering applying to MIMS at the iSchool but not sure if I match the criteria or not. I have three years of work experience working on the data end of international development and hence I'm looking for a masters program that equips me technically to pursue development solutions. My undergrad was from Mount Holyoke with a major in Politics and a few courses in Comp Sci and Communication. C.GPA was 3.74 and GRE 162 verbal 160 quant and 5.5 analytical. I'm afraid of the program being too techy but then I'm thinking that since I have the option to take electives I could bridge in courses on development and policy as well maybe. My other prospective programs are:

CMU - MSPPM Data Analytics Track

UChicago Harris - MSCAPP

MIT - MUP IDG

Fletcher - MALD

SAIS - MAIA

It would be great if people could share their experience with MIMS and also whats the likelihood of me getting what I'm looking for from these programs.

Thanks!