University College London - MSc Computational Finance

The course provides a strong mathematical and theoretical foundation in both computational finance, statistics, and machine learning. The professors are highly knowledgeable, and there is a wide selection of modules to tailor the learning experience to individual interests. It’s easy to build strong relationships with faculty, making this a solid pathway into PhD programs and advanced academic research. However, the program’s career services are a notable weakness. While there is the option to complete a thesis in an industrial setting, which can vary greatly in quality and rarely leads directly to employment, there is limited support for job placement and the courses offer little in regards to interview preparation.

From what I see, the Quant course for those interested in DeFi. A well designed course that has left me with a paper published and a job within DeFi. The faculty care.

The MSc Computational Finance at UCL provides a unique and necessary blend of mathematics, programming and finance knowledge for those looking to break into the quantitative finance industry, or for those who wish to continue with academia. Furthermore, the programme offers courses on financial engineering, market risk, numerical methods, machine learning, which are crucial to securing a quant role within a bank, hedge fund or trading firms. Additionally, the lectures are distinguished experts in their fields, being both enthusiastic and understanding, thus creating a very friendly environment for all to learn.

This MSc provides a dissertation final project, which can be done in collaboration with industry partner to give real-world experience in applying what you have learned throughout this course. Being based in the heart of London also provides a unique opportunity for networking with people in industry or potential employers.

Like any university programme, challenges are bound to emerge. In particular, the quality of some of the lecture rooms were not amazing, especially considering how much you are paying for the course (which is another point on its own). Moreover, the career service is somewhat lacklustre in certain aspects, and this in conjunction with the poor administration is really a let-down.

To conclude, my experience during this course was definitely a positive one, not just in regard to the skills it has equipped me with, but also to the interesting people I met along the way. If you’re looking to be a quant, you won’t regret choosing this course.

The knowledge conveyed during this program is excellent, especially for anyone who wants to continue a career in the financial industry, particularly in quantitative finance, and also for those aiming to pursue academia. This is because the curriculum offers a great mix of computational and mathematical finance, complex systems, physics, and machine learning. The lecturers are leaders in their respective research fields, which provides a unique perspective on the different topics mentioned.

Through the final project or dissertation, students can choose to either collaborate with important players in the financial industry or focus on purely academic research and publish a paper. This is very helpful for securing a full-time position in the industry or a Ph.D.

As with any program or university, there are issues, especially in terms of organization. For instance, for one course, we had to move to a new room for each lecture. Also, in my opinion, one should be sure about pursuing this master's as it is expensive.

Overall, it was a great experience. I got to know interesting people and I learned a lot.
I can recommend it to everyone!

The curriculum is exceptionally well-designed, keeping pace with the evolving demands of the industry. It incorporates a wide range of optional modules, allowing students to customize their learning journey according to their interests and career goals.

The faculty, especially those specializing in quantitative finance, are distinguished experts in their fields. Their commitment to teaching and the depth of their knowledge is evident in the rigorous assignments and the comprehensive understanding of concepts they provide.

Opting for an academic placement was a pivotal decision in my journey, leading me to pursue a PhD in quantitative finance. While the majority of modules were delivered online due to the pandemic, which somewhat limited direct industry exposure, the overall quality of education and support remained uncompromised.

In conclusion, my experience with UCL's Computational Finance program has been positive. It has equipped me with valuable skills and knowledge, paving the way for a successful career in quantitative finance. I wholeheartedly recommend this program to anyone looking to advance in this field.

Positives:

This quant finance program has people from a range of undergrad backgrounds therefore student have different strengths so you will be able to learn a lot from your cohort. I think there is power in diversity .

This program allows you to make a choice on whether you want the focus of the course to be more theoretical or practical based on your module choices.

Negatives:

There was little to no support from the career services, with students receiving zero exposure to industry other than potential master dissertation placements

Quality of lectures could be improved

Since the program only lasted one year it was quite rushed in terms of the material