MBA of Data Science & Analytics at USP/ESALQ, worth it?
A detailed and analytical review based on: experience, program content and results.
Introduction
Surely you’ve heard that ‘data is the new gold’ and ‘data science is the sexiest profession’ — those who work with data, or want to enter the field, wish to ride this wave. However, it’s not that simple to surf a tsunami, we are talking about exponential technologies that require constant knowledge updates, and trust me, there is always a lot of new stuff to learn all the time, many tools, and many sources of knowledge available.
In this context, a graduated engineer, passionate about data and statistics, decided to pursue an MBA in ‘Data Science and Analytics’ at USP in 2022. With the course coming to an end in 2024, I will present here my critical review of it — translated for data people.
Why I choose this course?
Nowadays we have access to a bunch of good courses to get fast data knowledge like Data Camp, Alura, even some free courses from huge players, wich I also strongly recommend — But its not about this I am talking about.
I was looking for something more, I wanted a long-term course that would have a significant impact on my resume and provide me with a lot of knowledge in an organized way — and well, if you live in Brazil, you certainly know the University of São Paulo (USP).
USP is the only university in Brazil ranked among the top 100 universities in the world, according to the QS World University Ranking, and is considered the best in Latin America.
I was sure that an MBA at USP would boost my CV, but what about the study plan and content? — Now I will tell you more about the course, and bring you more about it.
- Format and Platform
- The Content
- The Professors
- Tests
- Results and Conclusion
Format and Platform
It is a relatively long course, lasting 18 months, with more than 70 classes plus additional lectures — 385 hours plus 40 hours for the elaboration of the Term Paper — with one class per week, lasting approximately 3 hours. The classes are flexible and online, we can attend live or watch the recorded session later — which I always preferred due to my chaotic schedule.
What caught my attention the most was that despite being an online course, the class had a great structure with a chat feature and professors supporting with answers, class mediators who didn’t just lead the organization of the class but engaged and motivated the students, and always offered comforting words to the tired students — Here I would like to express my enormous gratitude to those who made our sessions brighter Amanda Dechen and Vitória Sabino.
The Content
I conducted a small study trying to bring visibility to the proportion in which the macro topics of the course were covered. We went through several important matters in the data field, and the most covered topics were undoubtedly about Machine Learning.
Whenever a topic was covered, the professors provided sufficient depth, including both theoretical and practical parts — hands-on. They always provided various references and brought in real-life cases, which helped and encouraged us to apply the topics in personal projects and at work.
The Professors
I was positively impressed with the teaching methods and the quality of the professors at USP — I had the idea that the classes would be very difficult to understand, but the professors were extremely careful, attentive, and had an exceptional understanding of the topics.
Only a true expert has the ability to convey complex content in an easy and clear manner.
And it’s no wonder, if you take a look at the professors’ résumés, they are jaw-dropping and make you proud to say that you had classes with such professionals — They are masters, doctors, founders, renowned autors and researchers, people who worked at giants like SAS, Microsoft, Amazon, IBM. One of them is an author of a globally adopted book ‘Data Science for Business and Decision Making’ (Cambridge: Academic Press Elsevier, 2019) Luiz Paulo Fávero , and we had also the honor to have classes with the 2% world’s top influential scientist (by Stanford University) Prof. Dr. Marcos Santos.
I left classes with my eyes shining and full of desire to apply the learned content. Incredibly in some classes I was surprised to leave it with tears of emotion in my eyes due to the words of encouragement from the professors at the end of a class — I studied early in the morning before work, at night before going to sleep, on Saturdays, and Sundays — and it wasn’t hard to do; it was extremely satisfying because, besides loving the topics, the professors greatly contributed to the engagement — and I am extremely grateful to them for that.
Tests
Ok, but life is not a bed of roses. The professors and the content are amazing, but we need to do our part. Attendance is measured by the completion of exams, and it needs to be at least 75%. We have classes once a week, and every class has a corresponding exam where the passing grade is 7. Additionally, we have a global exam at the end of the course and the defense of an individual thesis.
It seems like a lot — and it really is — but if you give the course the proper attention, everything will go well. The exams consist of 10 multiple-choice questions, you have 60 minutes to complete them, and three attempts to achieve the expected grade. The final paper is individual, but I found it more similar to an article, and I loved it because I really cared about the matter I was working on.
I still have two last evaluations to be done, but as long as I finished them I will post the results on my LinkedIn — and maybe I’ll write something about my thesis.
Results and Conclusion
Besides being a personal achievement, I was able to apply multiple tools learned throughout the course at work, where I received numerous recognitions for the implemented solutions. To illustrate this further, I will mention a few cases:
- Analysis and forecasting of projects using machine learning, bringing valuable insights to the company.
- Support for developing a mathematical calculation to weight the assessment of team development.
- Robust statistical analysis to evaluate the impact of project variants.
All of this was only possible with the gained confidence through the profound knowledge acquired. The course is coming to an end, and I already feel nostalgic and planning my next steps.
Answering the question in the title of this article, completing this postgraduate course at USP was one of the best things I have done for myself (so far).
Thank you for your time spending reading this article ♥
