NYU Tandon School of Engineering - MS in Financial Engineering

I didn’t grow up excelling in mathematics, nor did I come from a top-tier academic background. I went to a regular high school with a low GPA. I went to a regular college with no aspirations to continue my education. When I applied to graduate school, I applied to three programs. Two of them rejected me, and by the time I checked my Tandon portal, the acceptance deadline had already passed. I emailed anyway, hoping for the best, and somehow ended up here. It was surreal to realize I had been given a chance at something I had never experienced before: a truly rigorous, prestigious academic environment. This program has changed my life, and while I am deeply grateful, this is no advertisement. I want to give an honest and objective review of my experience. I will discuss the academic quality, the career landscape, and the student body.

When I entered the program, my understanding of finance and probability was minimal. Concepts like long and short positions, sigma-algebras, or even the structure of a stochastic process were foreign to me. By the time I finished the program, those gaps had been filled. Still, the academic experience here is a mixed bag. To begin with the weaknesses: the course structure can be inconsistent. Sections of the same class may cover different amounts of material depending on the instructor, and sometimes the pacing or organization can make it difficult to build understanding from first principles. Compared to the classes I took at Courant, where everything is rooted mathematically before being built upward, some of the MSMF courses focus more on application than on foundational derivations. Depending on your learning style, this can either be refreshing or frustrating. I also experienced situations where my class lagged behind other sections simply due to differences in instruction. This variation makes the academic experience heavily dependent on who you take a course with.

Despite this, the program has a major academic strength that I haven’t seen replicated elsewhere: advisement and accessibility. The faculty—whether full-time professors or PhD students—are genuinely willing to talk, help, and guide you if you put yourself out there. This is where the bulk of my growth happened. I spent hours asking questions, reviewing material, and learning how mathematicians actually think. The environment rewards curiosity. While the classes themselves vary, the people behind them are extremely strong academically and overwhelmingly supportive. This includes the leadership of the program, which is world-class in terms of research pedigree. If you want to learn, there are people here who will teach you. However, I assume you are reading this because you want ROI on your investment in a masters degree, not to enter a PhD program. And to get ROI, you need a job.

Career services are more difficult to evaluate. They try, and some students really do benefit directly from the structure. For me, it wasn’t the decisive factor in landing interviews or offers. The program is large, and naturally not everyone can be individually shepherded through recruiting. I found the alumni mock interviews extremely valuable, but beyond that, most of my progress came from my own preparation, networking, and project work. That said, the NYU name carries weight. Depending on who you talk to, some people associate Tandon with the Brooklyn campus, new and unfamiliar, or simply a solid program. Others see “NYU” and consider it an elite academic background. Either way, the degree absolutely got my foot in the door for enough opportunities that I was able to build a path in quant. It will open doors—what you do once they open is up to you.

The student body is large and diverse, both culturally and academically. Since this was my first time in a truly competitive academic environment, I don’t have much to compare it to, but I can say this: you will meet all types of people. Students who are frighteningly smart, students who work unbelievably hard, students who balance academics with real lives, and students who are still figuring things out. It feels like a real cross-section of the world, which I personally enjoyed. The size of the cohort can sometimes make things feel impersonal, but in other ways it creates a sense of scale—you learn to advocate for yourself, to seek out the right classmates, and to build your own circle.

To conclude, my experience at Tandon has been transformative. The academic quality is strong, though sometimes uneven; the career services help some more than others; and the student body is what you would expect from a large, diverse, competitive graduate program. What makes this place special, in my opinion, is the combination of accessible faculty, rigorous optional pathways, and the freedom to shape your own trajectory. This program won’t carry you, but it will give you every opportunity to succeed if you’re willing to put in the work. I came here with gaps in my background, and I left with the tools and confidence to build a career in quant. For me, that alone made the experience worth it.

Disclaimer: I advocate for a large student body, if the program was more selective I may not have gotten accepted. I consider myself as someone who has found success in this program, and I hope others may find similar experiences to mine. My review sits at 4 starts because there is room for improvement, but this program has changed my life.

Quick shoutout to Courant: the students and professors there are awesome! I hope there is more integration between our programs down the line. Much love

Putting disclaimer upfront, I wouldn’t comment on specific courses or professors, partly because I graduated a decade ago and things changed or escaped me, but more importantly casting lights into corners isn’t that helpful when the real need is an accurate picture of the overall landscape.

Sure. One can complain about the faculty, curriculum, career service, or tuition. But you would probably heard similar things if you talk to students of most other programs. And the almost perfect programs are just too selective to be broadly relevant.

The real question comes to understanding the programs, picking the fit one, and leveraging it to the best. The same program always have successful graduates every year, and can never ensure success for everyone, actually for anyone. It’s just a car, with its pros, cons, and price. We are the drivers, responsible for maneuver and navigation. Therefore why don’t focus on picking the best courses/professors and let the dean worry about the worst?

Looking back, I’m grateful for its quantitative rigor, diverse curriculum, and unparalleled location. Over the ten years, I also witnessed its improvement in candidate caliber, curriculum quality, and career service. I am giving a 4 star rating because it obviously has room to evolve, but the runway it paved is enough for takeoff.

I’m a current MFE student (graduating May 2026) with a focus on energy. I came into the program from a finance undergrad with strong motivation but a clear need for deeper mathematical fundamentals, real research experience, and better industry access. After 1.5 years in the program, I’m very happy with my decision to come here. Below are what I consider the strongest aspects of the program, in order, though the lower points are not weak by any means.

1) Community & Culture

Beyond academic rigor, the professors genuinely care about your success and take a personal interest in helping you reach your goals. If you are proactive about your education, they respond exceptionally well -- guiding you toward the projects, topics, and skill sets that matter most for your career.

The cohort is also large and diverse. We are one of the largest across MFE programs ranked on QuantNet. You meet people with different backgrounds, strengths, and industry experiences. These classmates become your study partners, project teammates, and, eventually, part of your professional network. People here work extremely hard, and I’m confident I’ll stay in touch with many of them for years.

The programs administration team are equally supportive. They consistently approach student requests with a “How can we help this student get where they want to go?” mindset from the top down. Whether that means adjusting schedules to accommodate a job, helping with cross-registration, or advising on long-term career goals.

2) Academics & Research Opportunities

The curriculum is rigorous and flexible. Industry-practitioner faculty are extremely strong, and more excellent professors have been joining recently.

If you want deep theory, you can take multiple PhD-level classes that count toward the MFE. If you want practical quant research experience, opportunities are abundant.

You can also cross-register for courses across schools in NYU: Courant, Data Science, Stern, and others. This adds a huge amount of breadth and depth that many other MFEs simply don’t offer.

Importantly, the program is what you make of it. If you are genuinely passionate and actively involved in the subjects you came here to study, you will get enormous value. If you lose interest but still expect top outcomes, you might not have the same experience.

Many of the practitioner professors also go beyond teaching — they help students find internships, refer them for roles, and in some cases hire them for part-time or full-time work.

Professors who have made a particularly strong impact that I'd recommend students learn from are: Bouchouev, Ivan, Yao, Conklin, Shimko, Tang, Perry, Abousallah.

3) Careers

Career support is a real strength at Tandon, especially if you’re willing to put in effort and engage early.

Our careers director, Sara, works incredibly hard on behalf of the students. She supports networking, interview preparation, and overall positioning for competitive roles. The internal job portal she curates is excellent. Many of the strongest roles each year (hedge funds, banks, trading firms, quant/data science positions, and more) come through it.

I will be joining an oil major in their trading arm, which was a perfect match for my energy focus and research interests. I believe the program prepared me extremely well for this path.



The NYU Tandon MFE program rewards motivated, curious, proactive students. If you embrace the coursework, leverage the research ecosystem, and engage with the community, the return on investment is high.

I’m grateful I chose this program and would make the same decision again.

Since the MFE program is highly career-oriented, most applicants aim to secure strong job opportunities upon graduation. I will focus on the program’s career-support advantages:

1) Industry-aligned curriculum
The course structure closely mirrors real-world industry requirements. The program invites numerous practitioners from both the buy side (e.g., former portfolio managers at top hedge funds) and the sell side (e.g., MD-level quants, risk managers, and traders). The coursework is hands-on and project-driven, allowing students to build impressive, industry-relevant projects that significantly strengthen their résumés and improve their chances of receiving interviews.

Because many professors come directly from industry—and some even run their own firms—they frequently hire students as interns or even full-time employees. This direct access to industry practitioners is an invaluable advantage.

2) FRE Careers Technical Interview Mentorship Program
https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering/employment-outcome/fre-careers-technical-interview-mentorship-program

I am also one of the mentors in this program. We provide free one-on-one mock interviews and interview preparation sessions for students seeking summer internships or full-time positions. Each mentor specializes in one or two technical areas.

This mentoring program helps students avoid low-level mistakes and, more importantly, narrow down the scope of their interview preparation based on specific job targets. Most mentors have many years of industry experience. As interviewers, we have spoken with hundreds of candidates; as interviewees, we have gone through hundreds of interviews ourselves. This depth of experience is extremely valuable for students, especially those who are new to the U.S. and just beginning their career journey.

My time in the NYU MFE program has been very valuable. The curriculum offers rigorous, technical courses for those who want to deepen their academic foundation, while also providing lighter-workload options for students who wish to focus more on job searching.

In addition, the alumni network is incredibly supportive, and many alumni are generous with their time and willing to share their career insights. In my own experience, I contacted alumni who had worked at the same company I was applying to, and their guidance on interview preparation and team culture played a key role in helping me secure opportunities.

Like many things in life, people can have different opinions about the same experience, and the NYU MFE program is no exception. I can only speak from my own experience.

For me personally, the NYU MFE program opened a door that would otherwise have been impossible to reach. Academically, the program offers a mix of professors with strong industry backgrounds who can bring real-world insights and connections, and others who are deeply focused on theory and dive into the fundamental logic of mathematical models, both perspectives are valuable depending on what you’re looking for.

On the career side, we have Sara, who provides thoughtful career guidance and organizes events that connect students with alumni and help us better understand the industry landscape. I’ve even heard from alumni who said that Sara is one of the main reasons they still stay connected to the program. She truly builds a sense of community that lasts beyond graduation.

I’m genuinely grateful for this program personally. Of course, no master’s degree alone guarantees an ideal job, you still need to find your own direction and put in great effort. But if you’re looking for a solid ladder to help you climb toward your goals, NYU MFE is definitely a great choice that can make a real difference.

I actually come from a DS background rather than a traditional quant path, and the NYU MFE program turned out to be an incredibly valuable experience for me, which might be helpful to students with similar profiles who want to explore data science roles within the finance industry.

The best part of my FRE experience was definitely the career placement and alumni network. I found my summer internship through an internal posting on the FRE Net (thanks to Sara’s help!) — it was a financial DS role that gave me hands-on exposure to modeling in a real business context. Later, my full-time opportunity came from a referral by a senior classmate, who also guided me through the preparation process. Without this program and its community, I truly wouldn’t be where I am today.

That said, it’s important for future applicants to keep realistic expectations. Securing a full-time role in the U.S. is competitive and not something any program can guarantee. But compared with peer-level MFE programs, FRE does a solid job providing access to opportunities and mentorship for those who are proactive.

Overall, I’m deeply grateful for the program — it opened the door for my transition from data science into the finance domain, and gave me the foundation for the career I have now.

NYU FRE has amazing career support and a solid academic foundation. From day one, we had access to workshops, resume reviews, and mock interviews that really helped me prepare for the job market.

The courses are practical, and professors bring valuable real-world insights. Overall, the program has prepared me well for my future career.

Pros:
- location
- NYU name brand
Cons:
- They mention resources that will help u landing a job, but nothing really is helpful. They do things on their own timeline and if u want access to materials u have to wait till Sara is ready. They advertise being helpful but most of the times the replies and materials shared are generic and can be easily found online.

I think they are trying hard, especially with new management. You can tell the person at the top genuinely cares about students but the people executing this aren't very supportive - more focussed on protocols and ticking off a box than genuinely ensuring student success.

- variety of electives to choose from.
- the placement coordinator is really supportive and helpful.
- academic advisors are great!
- cohort is quite competitive.
- the department encourages participation in multiple events
- having the option of taking Courant courses is unique to NYU

I don't know what happened to this program but it seems most instructors are reluctant to give A or even A minus. Most of the course grades were like B+, B or B-
If the program has a harsh grading scale, it is not suitable for students to seek jobs. (We all know students want to find jobs through this program but the program itself is making it hard for no reason.)

NYU FRE has the best career service! The program is somehow designed for preparing for work, which I really need.

During the Bootcamp, we work on technique interview related questions with professors. And we are asked to attend career workshop before the first semester, which is highly helpful for international students to understand how to find a job in US.

Sara, our career advisor, is super professional and sweet. Whenever I have career related question that bothers me for a long time, she can always help me out! Also, we have proficient resources for job hunting, including mock interview (both behavioral with Sara and technique with alumnus) , career workshops, templates of CV/cover letter/thank you letter. She also organized us to prepare for interview questions for share. I was impressed by the time when I made a mock interview appointment on Friday, and I was reached out by an alumni in only several hours. So efficient! Our alumnus are also super helpful and they are willing to share!

Feel proud of FRE!

I am a current first year student in the program and so far my experience with the program has been bad (being generous). The thing which the program advertises the most is large cohort, small class sizes, industry profs and large number of courses to choose from.
1. Large cohort and small class sizes: the obvious problem with this is that if there is a course which is high in demand, only 30 (or 20 in some cases) people will get it. There maybe multiple sections to the course but the content will vary vastly from one prof to another with one prof ending the course at risk neutral pricing and the other doing stochastic modelling. The course syllabus given is mainly for reference and most of the professors just mention what some approach or model is rather than going through the mechanics and helping us build intuition. You can google 10 different topic names and read the first page of the topic and be done with the course. In addition, the admissions criteria for the program is set very low and people with little to no background in either math or finance end up in the program which drives the stats lower. The cohort would be the most average cohort you can get.
2. Industry profs: the thing about industry profs is that most of them are very disconnected from how one should teach and structure the course. Most of the courses taken by them are 1.5 unit course (half semester) and the courses are very rushed with majority of them not completing the syllabus. A few of the profs don’t even have a syllabus but would teach topics what they feel like teaching. I am enrolling in the program to learn the concepts and build a toolkit, teaching some tips and tricks for on the job work will not help me clear interviews and every firm has different code base so majority of what you are teaching might not even be relevant. (Although there are some very good profs like prof. Tang, Adams, Mandel)
3. Large number of courses: Most of the courses are overlapping with each other and when asked for recommendation on what to take from the department the usual answer is choose what you want. In addition, as I pointed out earlier that majority of the courses are half semester courses, you just end up learning the jargon of the courses without building any skills. I am in my second semester with 12 credits remaining and can hardly fill it with 6 credits of acceptable courses for the next year.
The career service of the department is also bare minimum. There are no networking events organized and very few job postings (although LinkedIn has much more). I have gained much more valuable information by following Ashley Cross on LinkedIn (CMU’s career advisor) than my career department.
Advice to incoming students: Select your courses carefully and take advice from seniors on what courses to take. Start networking and preparing for interview from the day you receive admit. And lastly hope that we get a new program director who is decisive and can improve the program.

I would like to share a few things for incoming or prospective NYU MFE students!

1. We have a large number of courses you can choose from for each semester, like machine learning, derivatives pricing, risk, quantitative trading, portfolio management... I want make it more specific, for machine learning, we have different courses like Machine Learning for Finance, Advanced Machine Learning, News Analysis.... If you like trading, we have Algorithmic and High Frequency Trading, Active Portfolio Management, Fixed Income Quantitative Trading, Quantitative Trading Strategies, Quantitative Equity Investment, and etc. I believe you will find the courses you like! These courses are all taught by professors from industry with senior title.

2. We have two Career Websites. One is by NYU, the other one is by MFE department. Most of the time, we use our department career net. Our career replacement director, Sara, is the most helpful career director I have ever met. She organizes many on-campus recruiting events for our students, post many "only for NYU MFE student" jobs, provides helps from resume to interviews, literally, everything. She is not only helping you with job findings, but also "pushing" you to find a job. If you do not apply jobs through MFE career net, she would send you an email to understand why and she would be more than willing to help you with any problems! She even contacted many international companies, like securities company and funds in China to give more opportunities to students who want to work outside US.

3. The third one is for students who would like to apply for PhD in the future. As we all know, most of students get a MFE degree and then go to the industry. But it is not uncommon that MFE students in our department decide to pursue a PhD. We have capstone research projects, thesis, industry research opportunities, and other research opportunities which can equip you with a strong research ability. I really appreciate Professor Carr's time and helps! It was an honor to be his student! He helped me with everything regarding my PhD application. For this semester, he is working with 4 students who apply for PhD. We all got offers, like Johns Hopkins University, NYU Courant, University of California, Santa Barbara, Boston University, and University of Utah. Without Professor Carr's help, we could not even make this happen! So I would say, our department is not only helping students get into industry, but also providing numerous helps to students who want to get a PhD!

I would like to share my experience not as a NYU MS FRE student but as a NYU Tandon School of Engineering international grad MS student from another program. Last 2017 Spring semester I took Corporate Finance at the FRE Department, it was a really great course that I highly recommend, the Professor is a master on the topic and with tons of practical experience of real cases and advisory experience to financial institutions around the world, he taught us how to really apply financial thinking and tools to real cases and CFO's challenges.
I believe important to share this really positive experience, as a student who is trying to pursue a career on investment banking and project finance, I am convinced that through the practical expertise taught at the NYU FRE Department students are really wining what we should be looking from our graduate experience, real world tools and skills in order to succeed on our future careers.

It's so funny that everyone wants Peter Carr to carry the whole department. Everyone has only one answer to all the problems - "we have Peter Carr". Also, it is so obvious from the reviews getting deleted that there's something seriously wrong with the department. It's a scam running for past couple of years under the name of NYU. Don't try to make a fool out of everyone by writing fake reviews. Peter himself knows the truth. Below is a detailed review -

1. If you want to be honest and work hard - you'll fail terribly because most of the students will cheat off their exams and get good grades.
2. Some professors do not really want to teach and it seems they're doing a favour by coming to the school.
3. No career help from anyone here are at the department. Believe me it's a scam.
4. This program is not for anyone who aspires to become a quant.

And lastly why are all the good reviews coming up now? Good marketing campaign. Mixing up education and money. Job well done.

This is the third edition of my comment. Try to be more objective.
1. In response to some comments below, I appreciate some of their ideas, which helps me to suggest Peter on how to improve our program.
2. For others, I have to say that any program will never guarantee you any job placement. It’s not like you paid the department 60k USD and a red carpet will appear automatically to lead you to Wall Street. You have to work hard. Some people have already land great jobs in quant or other fields. If you don’t know any of them, then it is your problem. If any jobs other than a quant is not “placement”, then there will be far less employment records in other programs as well.
3. To the so-called “professor”, I wish you can present any evidence, or simple pay us to create “evidence”.
4. To the guy who claimed that many recruiters refuse to take our resumes, please name them, or their companies so you claim will be more compelling, and we can save time avoiding these teams. Please. Please.

True, the department is collecting students’ reviews to bring more changes to the program, but it is not a marketing campaign trying to furnish our reputation. I have sat with Peter and spent a few hours to discuss my experience so far in this program, and how he can improve it.

I’m here to express my own opinion, not to flatter, not to slander. I appreciate what the program has brought to me (quant skills, access to great resources, scholarships, etc.), and I dislike some other aspect (some professors’ accent and attitude, delays in some daily operations). That’s why I’m sharing my experience and giving 4 stars instead of 5, while I know some guys genuinely want to contribute nothing other than 0 stars (but sadly, they can’t give 0).

The program is rising from mediocre, with the help of some talented and determined people. This summer (2017) the incoming students are taking an online boot camp. I’m sure they will be better prepared for internship application and interviews. I’m very happy that in less than a month Peter have put what we have discussed into action. He loves this program.

My thoughts are presented as follows:

What were your favorite courses and instructors?

I regard Prof. Jerzy Pawlowski (R and Algorithmic Portfolio Management), Prof. Tang (Financial Computing and Big Data Analytics), Professor Mandel (Fixed income quant trading) as the best instructors of this program. Be sure not to miss their courses.

What courses are missing?

For courses, I would like to have Python, machine learning course (Peter had a new professor and he will open this course in Fall), maybe deep learning. It will be great if we can organize our students to test strategies on open platforms like Quantopia.

What would you improve in the program?

Some advice from faculty members are very helpful, like joining meetups. We can make the advice into 0 credit courses to push students into learning things.

How would you improve the job placement process?

The job placement process is hard to take off quickly. We had an awesome director, but she will not provide job offers to all of us outright. We need to focus on two parts: job application and interview. She is working very hard at the job application side, and we need to improve the interview side, like using Financial club to organize interview training/peer interview sessions.

At the very end, I would like to notice anyone who will be reading this review: all reviews are subject to everybody’s very own experience. As time passed by, and as the situation changes, some of these reviews may not be valid anymore. Take our words with care.

Currently student here. Someone asks to name some students who go to bb. Here is the situation. We have Barclays Capital, Goldman Sachs, Moore Capital, JPM. That's just what i have known so far.

About the courses, i would say some of them are great and some of them are easy.
Programming: Financial Computing(C++), great course taught by great professor. Algo Portfolio Management, which requires high level R language and relevant portfolio knowledge. Fixed Income Quantitative Trading, use python to write trading strategy.
Math: Stochastic, Continuous time finance are really great and important course for quant.(btw, CTF is taught by Peter)

This program is definitely in progress since peter came here and we got a lot of opportunities in career. And recently Sarah was invited to be our career mentor who was responsible for campus recruiting at Morgan Stanley.

I would say it's a great program overall.

I graduated from this program in May 2016 and right now work in Susquehanna International Group after I left Soc Gen.

The overall experience in the program is positive.

I am quite disappointed by those 1 star/ harsh reviews below. Especially the people who blame this department did not place them with a job. My suggestion is that If you really want a job, then go talk to people, go networking, go prep for the interviews, go find internship, read more books at home. No such program is going to spoon fed you and make sure you have a job right after you graduate.


Pro:
Recommendation of professors:

1. Professor Hoff (commodity ) : super nice and knowledgeable, his lecture is divided into 2 part, first half is industry insight and second half is the Math.
2. Professor Pawlowski (R, Algo portfolio) : everything you need to know in R related to Finance and quant trading. His lecture is really useful, I share it with my colleague and having traders and quant using this as template of our code.
3. Professor Mandel: Cover fixed income in solid and practical, it is the kind of knowledge you need before you join a fixed income trading desk.
4. Professor Tang: C++, great teacher, teach the material well. A good refresh for student who already know basic data structure and fundamental object oriented programming.


Overall the courses are great except Accounting(useful for Credit trading and Equity trading) but now accounting has been cancel which is a good thing.

Since this program has so many courses to choose from, it would be helpful that you ask yourself what you plan to get out of it after 2 years right from the beginning and build your profile and chose courses according to that goal. (Technology, Quant strategist, market risk management or quant trading)

Great location, just being in New York is a big plus for such program like Financial Engineering. This mean lot more job opportunity and the classes are more practical.

Small Class size, even the program is big but the student in each class is around 20

Lots of industry professors, so you have a good idea of what is going on in the street.

With Peter Carr being our new Department Chair, he restructure this program and already brought in talented industry professors from the street and initiated industry projects with companies. Also, Sara new Career Placement Director and she did a great job in reaching out to company and alumni to assist with placement.


Con:
1.5 credit course( 7 lecture) seems too short. Could restricted such that 2 professor teach one topic like in Courant.

Need one python classes. You can learn at home, but would be a great idea to structure the class around Python or R.

More courses on fundamental Statistic, probability theory, and Stochastic Calculus, even it is listed as requirement but students come from different background.

Cheating in the class should be punished more severely.

I am a Fall 2016 student in NYU Tandon's FRE program. Overall, my experience has been pretty good... academics (including the coursework, professors) are good. Yes, few professors/courses might need some tune up, but there in multiple course offerings by different professors which can be pursued.

The career cell at NYU performs satisfactorily however it can do better. Sarah, the new placement director at FRE is doing the best she can considering the uncertainty in the job market (especially for International students, which is 99%+ of the enrolled students)

If you build your profile well, take the right courses (according to your interests), put effort in your academic projects, I don't think there is a downfall to the experience.

Recommendations for Negative Reviewers:
1) Don't expect to be spoon fed all the way through the program. No one can cover 100% of the stuff in class. I have seen people crib that they could not correctly answer a question in an interview and blame that it was not covered in class. (Thats just total BS). If you are gonna blame someone ....blame yourself for not cracking the interview.

2) No program will promise you a job at graduation. If you want a job you will need to get go out and get it....Applying through portals only gets you upto a certain point...

3) Most skills are picked up in Finance are OTJ. If you are looking for an entry level job, the chances are you will be interviewed on your academics (mostly basics). If you know your stuff, you will sail through..... There is difference between academic knowledge and industry practice.... you will know it once you enter the industry.


Recommendations for the Program:
1) Scrap the 1.5 credit courses: I don't think there should be any course with 1.5 credits.... You can make the syllabus more detailed and make them 3 credits. Personally, I don't think 1.5 credits does justice to any subject.
2) The program size is too big: I mean 150+ students (you must be kidding me). Most programs on an average have 60-80 students graduating each year. Its difficult to place that many students in a year (no matter how high the quality of students you have... which is not the best anyways).
3) Faculty: Please review the faculty, ...I have personally not faced any issues like any of the comments below but I guess they are far too many to be ignored.

Overall, the program can be a home run or a strike out but it depends more on the student and less on the academic program/department/faculty... yes they are always to guide and help you out in case of questions. The program is undergoing major changes in terms of coursework as well as the faculty, Peter Carr is making changes which I feel will move the program in the right direction.