MLI Alumni Stories
The Machine Learning Institute Certificate in Finance (MLI) Testimonial and Alumni Stories highlight the transformative experiences of professionals who have completed the program. These testimonials showcase how the MLI has helped alumni develop advanced machine learning skills tailored for financial applications, enhancing their careers in quantitative finance, risk management, and trading. Graduates share their success stories, detailing how the program’s rigorous curriculum, hands-on projects, and expert-led instruction have deepened their understanding of data-driven decision-making and AI-driven financial strategies. Their experiences serve as a testament to the program’s industry relevance, equipping participants with the expertise needed to stay competitive in the evolving world of financial technology.
Obtaining the MLI is a solid demonstration of continuing professional advancement and one that will keep both you and your employer ahead of the competition. We are confident of the high quality and practical value of the MLI. It is a privilege to be able to bring this programme to so many.
Testimonials:
I had the opportunity to participate in a 7-month course focused on machine learning applications in finance, and it has been a truly transformative experience.
The programme was rigorous, providing a deep dive into the mathematical foundations of various machine learning techniques. We often explored concepts from first principles, which gave me a solid grounding in both theory and application. The course also exposed us to cutting-edge financial machine learning topics, with the chance to learn directly from the original authors of key research papers. This combination of strong theoretical depth and access to the latest advancements was invaluable.
The faculty were world-class, with several experts in the field of financial machine learning leading the programme. Having the opportunity to engage with these thought leaders and ask questions about their modelling decisions was incredibly insightful. Their expertise and willingness to share practical insights helped me gain a deeper understanding of how to apply complex techniques to real-world financial problems.
What truly set this course apart was its practical focus. While we always had a solid theoretical foundation, the emphasis was consistently on understanding how these algorithms work in practice. The programme equipped us with the tools and knowledge to think about applying these techniques in diverse financial contexts, such as banking, treasury, and insurance. The Jupyter notebooks provided throughout the course allowed me to gain hands-on experience and build intuition, ensuring I could confidently apply what I learned in my day-to-day work.
Overall, this programme has been a critical step in enhancing my expertise in financial machine learning, and I would highly recommend it to anyone looking to deepen their knowledge and skills in this rapidly evolving field.
Tomi Adewusi, Associate at Morgan Stanley
“I liked the length of the MLI program and could see that the syllabus covered many topics from supervised learning and neural networks all the way to quantum computing at the end of the program. The faculty members were very impressive in their fields; people I had heard of and knew from the industry. So, I enrolled.”
Diana Enes: Head of Derivatives Valuations Unit, European Investment Bank
“Certainly, you can do machine learning and AI education using popular online platforms, but what ultimately keeps you engaged is if you have good instructors, weekly lectures, homework, and, in the end, you will receive a certificate, something you can show to your employer or discuss in job interviews.
Finally, I’d make note of the natural language processing lectures towards the end of the course. These days, everybody is talking about Chat GPT and it’s certainly one of the most interesting and exciting fields.”
Florian Grünewald: Senior Quantitative Pension Consultant, Siemens
“When I signed up for the MLI, I had been working for 11 years in the actuarial space and head a team working on internal models within an insurer in the London. My educational background was fairly quantitative, as I had an undergraduate degree in economics and actuarial… The Python primer was more than enough to get me going. Prior to that, I had used MATLAB and Visual Basic and there was a fair amount of similarity between MATLAB and Python in terms of the way code is vectorized in order to make calculations efficient. I had also done quite a bit of reading in previous years on neural nets and I was familiar with classification techniques, but this gave me a chance to put these ideas into practice.”
“Currently, I work as a portfolio manager at an asset management firm in Latin America. I have developed my career in investment management for 6 years and I believe that machine learning is a new way to improve your set of skills and also it gives you new tools to analyze financial markets. The importance that machine learning is having in the investment decision process and how these tools are changing the finance industry should motivate investment management professionals to learn these new techniques.
In this manner, I totally recommend the Machine Learning Institute Certificate because it gives you the tools to learn in a practical and easy way the several models that can be used in the finance industry. I learned from linear regression and regularization to Neural Networks and the professors are very experienced and proficient in using these tools. Finally, I will be using the knowledge and tools that I learned in my investment and research process as a portfolio manager.”
“Currently, I am a consultant combining data science and machine learning. Formerly, I was a Treasury executive focused on developing data-driven insights for asset and liability management, and managed a 16-billion retail option portfolio to maintain minimal rate risk in the banking book.
I highly recommend the Machine Learning Institute Certificate in Finance to anyone who wishes to effectively apply the latest tools in predictive modelling and data science.
This program covered a good balance between theory and practice. The practicums provided excellent jumping off points for my own use cases. I often started with code provided by the instructors to do what I needed, especially in natural language processing and cross-validation.
The material and techniques were current and taught by experienced finance industry practitioners who actually use the techniques they taught.
Using the knowledge and techniques I learned in this program, I now possess the ability to explore current research in ML/AI more effectively and productively.”
Cameron Wicentowich: Consultant – Advanced Quantitative Solutions
“I was searching for a course regarding the ML/DL application to finance. I have found an excellent choice, the one proposed by MLI. The course provides a global overview of the ML/DL technique applied to financial cases starting from the beginning; up to a medium depth. Participants who want to learn more about specific topics can ask instructors for additional sources and material. A previous exposition to python and ML/DL is advisable, but it is not mandatory.
Giovanni Paolinelli: alck Renewables
“As a financial systems engineer until now I had developed systems using financial engineering. In the future I will need to develop financial systems using machine learning, so I took MLI to acquire the necessary skills.
During your MLI journey wherever you are in the world, you can take the practical machine learning lectures from university professors, bankers and instructors from well-known global companies. There are many machine learning courses, but there are few courses where you can learn machine learning on the subject of quantitative finance, and I think that is the greatest attraction of MLI. MLI’s lessons begin with Python and performance tuning, and cover a wide range of areas necessary for financial practice, such as supervised learning, unsupervised learning, natural language processing, deep learning, reinforcement learning, deep learning volatility and time-series analysis. The MLI lectures are given in the evening UK time, but the time difference is not so important because the videos can be used.
I’m a non-native English speaker, but now we also have automatic subtitles. I recommend MLI as a machine learning course for financial professionals. I have started my machine learning work and will continue to make full use of machine learning in the field of finance.”
Professional: NS Solutions Corporation (a subsidiary company of Nippon Steel Corporation)
Download Event PDF