COMPARE UCB MFE vs NYU Tandon MFE

Rank
Program
Total Score
Peer Score
% Employed at Graduation
% Employed at 3 months
% Employed in the US
Compensation
Cohort Size
Acceptance Rate
Avg Undergrad GPA
Tuition
Rank
4
University of California, Berkeley Berkeley, CA 94720
4.17 star(s) 41 reviews
4
University of California, Berkeley
88 3.6 79 92 83 168.2K 86 17.96 82.90K
Rank
9
NYU Tandon School of Engineering Brooklyn, NY 11201
3.43 star(s) 30 reviews
9
NYU Tandon School of Engineering
77 3 67 89 64 119.5K 146 28.11 81.58K
Joined
5/3/24
Messages
1
Points
1
Hey everyone I just got accepted to NYU Tandon's MFE program and I wanted to know if anyone had any tips regarding maximizing my education experience here. I know it's 1.5-2 semesters long with 33 credits, students typically take 6-9 credits per semester, and they offer a wide range of courses.
In particular, I was interested in the machine learning trading courses and crypto trading courses. Has anyone taken these courses previously? Additionally, how is the courseload here? Are you stressing out everyday trying to meet deadlines?
Also, I hear the career services are great. Can anyone else attest to this? I heard you start interview prep first semester in to secure internships in the spring.

Thanks, and one more thing--I'm debating on sending an application to UCB Haas's MFE program. I heard their career services are unmatched, but I was wondering about their courseload and offerings. How much information could I realistically retain from 1 year?
 
I'm currently at Tandon MFE. 9 credits are minimum per sem except for full time status. Course load varies drastically depending on courses. It can range from maybe 1 hour a week to 20-30 hours per week outside of class. There are plenty of very good ML and programming courses.
Some courses are a breeze, some may make you want to pull your hair out (depending on what your previous knowledge base is).
Career Services are a hit or miss, the market is really poor right now. But the bootcamp is quite helpful regardless.
Pro Tip: Decide early on your academic goals, what courses do you want and not. Spread the tougher courses uniformly so as to not create too much burden in a single sem and too little in others.
 
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