Hey folks,

I have been meaning to write about this specialization for a while now, for various reasons. Firstly I just want to share my experience and all the things we learned, we got to do, the people I met, the connections I made and so on. Secondly I want it to be a good starting point for anyone who plans to take up this specialization and want to know what the spec entails. This is particularly aimed at the PGDM-IB students at MDI who come to ESCP for an exchange year who need more details on the spec.

As an IB student, if you want to know how the specialization is chosen and how the overall ESCP journey is structured, you may read relevant sections from this article I wrote a while ago. This is purely based on my experience, and I am guessing good parts of it will be relevant in the immediate future as well (unless drastic changes occur).

0. Init

The AI and Big Data for Business Innovation specialization[1] is a relative new spec offered at ESCP. We are the 6th batch who up this one. I believe it comes under the purview of Information and Operations Management. Prof. Markus Bick[2] heads this specialization along with Prof. David Lehmann[3].

The specialization has 4 courses:

Enterprise Systems and Future Trends by Prof. Markus Bick - 30 hours
Leading Digital Innovation Projects by Prof. David Lehmann - 30 hours
Big Data and Business Intelligence by Prof. Javier Amaya[4] - 30 hours
Artificial Intelligence and Machine Learning by Prof. Daniel Pesch[5] - 30 hours

Along with that, we have 3 mandatory core courses:

Business Law[6] by Prof. Peter Zaumseil[9] - 15 hours
Sustainability[7] by Prof. Carolin Waldner[10] - 15 hours
Advanced Organization and Management[8] by Prof. Thomas Gigant[11] - 30 hours

So in total 120 hours of specialization and 60 hours of core courses making it a total of 180 hours for the semester, that is the requirement. So at the time of choosing the spec, if you get a spec here in Berlin, then you are set for your 180 hours.

Officially, the first day at ESCP Berlin was 13 Jan 2025, Monday. But each specialization starts at possibly different dates. The Selling to Customers specialization started on 15 Jan 2025, the AI and Big Data spec this time started on 20 Jan 2025. But keeping 13 Jan 2025 as the start date, my suggestion would be to sort your home, anmeldung/registration, blocked account activation, SIM card - all these before your specialization starts so . Plan your arrival in Berlin accordingly, that is only if you get your visa on time :P

1. What does this specialization entail?

Its an out and out technology-focused specialization. It is for people who are interested in Data Analytics, AI & ML, Information Systems and Business Processes, and becoming a good product manager. There are managerial skills that you will learn here but it is more or less a tech-savvy spec. I obviously have all the material of this course, but I won’t be sharing all that. I will give a good peak into what the spec is about - the syllabus and structure of courses.

1.1 Artificial Intelligence and Machine Learning

A classic course by Prof. Pesch. The course entails theoretical introduction to machine learning. Out of the 10 sessions, 5 were regular lecture-style classes, 5 were practical programming sessions. The way it is structured is in a day, the first session, typically from 0900 to 1200 is the lecture session. From 1300 to 1600 is the practical session. We start with basic python programming and build better each day. We get an introduction (theoretical and practical) to supervised, unsupervised and reinforcement learning along with a detailed session on deep learning and artificial neural networks. We worked on a variety of machine learning models, algorithms and applied them on several different datasets.

The evaluation is divided into a group assignment and a closed book written examination - both of which will test your understanding of the subject and your application skills to a possibly real-life problem.

1.2 Big Data and Business Intelligence

Great course by Prof. Amaya. This is a highly practical course, it won’t be wrong if I say we apply a lot of what we learn in the AI & ML course here (and more). It focused on the entire pipeline - starting with some kind of big data, what kind of pre-processing needs to be done on what kind of data, what kind of model is helpful for what type of problems, where do you even store this data (a peak into database structure and systems), a lot of emphasis on AI-ethics, a pretty big topic these days. I feel most of Prof. Amaya’s classes are like this: He shows an example of how things are done, and we spend most of the time on a variety of examples experimenting and trying out things - this was until half way through the course, post which things got pretty serious. We ended up learning quite a bit about Image Procession and Computer Vision, Convolutional Neural Networks and so on. I think we ended with Text Analytics, Transformers and Large Language Models and a peak into how they work. The course peaked because we ended up learning a lot about the things we see around today.

The course evaluation is similar to the AI & ML one. Just listen in class and ensure you understand all that the Prof has taught, you’ll be good to go for the exam.

My suggestion is to not miss any class of this or the AI & ML course. Both went hand in hand, both built on each other’s sessions, so if you miss a class on Random Forests in the AI & ML class, it can get hard to see how to use it and apply it in the example in the Big Data class. And their classes are super interesting.

1.3 Enterprise Systems and Future Trends

A highly relevant course by Prof. Bick. It is not particularly related to the rest of the three courses. It focuses on Enterprise Resource Planning (ERP), Business Process Modelling and Management, Process Automation and so on - basically a proper course for anyone interest in Management Information Systems. The classes are generally the Prof giving a lecture for about 1.5 hours, and then certain type of practicals are done. For example, he introduced us to ERP and we had a 2 hour practical session on SAP, you get a hands-on experience on SAP, you work on a neat case study and so on. Prof organizes a number of guest sessions (I think 3/10 were guest sessions) - from very interesting people - SAP, Celonis, Salesforce this time. We ended up looking at one of the latest things Salesforce is doing - their product called AgentForce where they use LLMs for Agentic Process Automation[9]. Apart from that, his classes are filled with interesting case studies. Lots of practical cases and hands-on stuff in the field of informations sytems.

Evaluation has a group assignment and a closed book examination.

1.4 Leading Digital Innovation Projects

This is the perfect course for people who want to be product managers, who want to be part of/run design thinking teams and so on. A lot has been discussed so far - Leadership, design thinking, on user journeys, user personas, stakeholders, entity-relationships, wireframing and so on. I am guilty of not focusing in this subject, so I can’t talk about this the way I can for the other courses. I will update this after going throught the coursework again sometime later.

Evalution has a group assignment and an individual assignment, there are no examinations.

2. Schedule

This spec, that too this year was scheduled in an weird manner I think. Most of the other specializations have classes on 3-4 days a week, and that goes on till 10/15 April 2025. But ours is not like that. The AI & ML and Big Data for Biz Intelligence courses got over (30 h + 30 h) by 08 Feb 2025. We had the final examination for AI & ML on 10 Feb 2025 and for Big Data course on 17 Feb 2025. Our spec was pretty hectic until 23 Feb 2025 - we had classes 6 days a week. But post that, now (it is 01 March 2025) we hardly have any classes. So the sessions distribution is very uneven unlike other specs where its evenly distributed over time. This shouldn’t really matter in any decision making, but thought of sharing for the sake of completeness.

3. On the core courses

Each core course has 8 2-hour sessions. Well, there is nothing much to share about these. All three are interesting courses, the professors are quite interactive and make the classes interesting. The Advanced Management course just has a group and an individual assignment and no exams, whereas Sustainability and Business Law have a group assignment and a closed book exam.

4. Conclusion

This is about the AI and Big Data specialization, this is how a typical spec is structured. This specialization is for folks who are interested in product management, Information Systems/Enterprise Resource Planning, Business Processes Management, Operations Management, Business Intelligence/BI and Analytics, Data Science - it is essentially a tech-based management specialization. I have a background in computer science and I am interested in processes, optimization and analytics - which is why I ended up taking this.

At MDI, you’ll be given a list of specializations to choose from roughly in the month of July (that is just weeks after you enter MDI). I can say not one really knew what these specializations entailed, they probably knew the names of the courses in it and a very vague description of it. I wanted to come to Berlin and there were only 5 specs offere in Berlin, and I anyway had a computer science background and wanted to pursue something managerial yet technical, so this course satisfied that condition. Without knowing what the spec actually is, I took it up. But that is not always a good thing to do. I want folks to be well informed about each spec before they choose it, and I believe I have done my bit towards that through this post. If you want to take this or any spec, I would urge you to check for people on LinkedIn who have taken the spec you are interested in, and know enough about the spec before making the choice.

Feel free to contact me in case you have any more questions about this spec or about ESCP in general.

Cheers,
Adwaith

5. References

AI and Big Data spec official page: https://ent.escpeurope.eu/Syllabus/SylView/view/11767361/2
Prof. Markus Bick: https://www.linkedin.com/in/lehmanndavid
Prof. David Lehmann: https://www.linkedin.com/in/lehmanndavid
Prof. Javier Amaya: https://people.ucd.ie/javier.amayasilva
Prof. Daniel Pesch: https://danielpesch.com/
Business Law: https://ent.escpeurope.eu/Syllabus/SylView/view/11763322/2
Sustainability: https://ent.escpeurope.eu/Syllabus/SylView/view/11763321/2
Advanced Organization and Management - Managing Change: https://ent.escpeurope.eu/Syllabus/SylView/view/11763131/3
Prof. Peter Zaumseil: https://www.htw-berlin.de/hochschule/personen/person/?eid=3639
Prof. Carolin Waldner: https://escp.eu/waldner-carolin
Prof. Thomas Gigant: https://www.thomasgigant.com/