Data Science Retreat

The Data Science Retreat is one of the few full-time data science courses in Europe. The 3-months intensive program is... intense. The courses are taught by senior data scientists from industry or from professors in the field. They are taught in blocks of 1-4 days and the topics cover a wide range.

Where the order of the courses is sometimes a bit confusing, and not all lecturers are of equal quality (both in terms of depth of knowledge and in terms of how they teach), the retreat does give a very good and broad overview over the important field of data science, AI and ML.

During the 3 months course, all students are required to do a project that results in a public presentation in the final week where industry is invited (networking for a job!). The 3 months are therefore split up into about 50% lectures and 50% project work. Mentors/ Tutors are assigned for the project work for weekly one-on-one meetings; this is also very helpful. 

The batch-size is small (6-8 participants) and there is therefore plenty of time to interact with the lecturers, discuss and ask questions. 

Things might appear chaotic at times, but overall it's a very good experience. 

Furthermore, Berlin is a fun city and very reasonably priced. 

Pros

• I attended a recent batch which started in September 2016
• High standards for acceptance was great - meant we could move fast and learn a lot not only from teachers and mentors but also from other participants
• Great benefit is lots of teachers, each with their own speciality - you get cutting edge advice and material about things the teachers are using themselves in their full-time jobs
• High quality of mentors and teachers and support for the portfolio project
• Great curriculum and decent job support

Con

• Not for everyone - Requires a lot of hard work to get the most of it, but a massive plus if you are very motivated  - the course moves at a pretty decent pace and you are not spoon-fed how to do everything, it requires working hard on exercises and a hands-on approach. However, this means you cover a lot of ground and learn very quickly how to figure things out as fast as possible, as you would in a real job

I was a participant of a batch in 2016.
My overall expectation was to become an expert in predictive modeling.
But there my expectation was not clearly met, because I found out.
However, the hands on experience offered to me was really useful.
What we covered was Random Forest, SVM, Deep Learning.
In the end, there is no free lunch. There is no shortcut to master all the topics.
But all in all there is a lot of pointers to various directions.
So the total experience is to extend my horizons, and it amazingly did.
I now know where to look for further information, what is possible.
You get to know which cutting edge technology is being used by professionals and how they apply it.
It was a multiplication of knowledge in general and I am satisfied with the outcome.
I see the portfolio project as a very useful tool to associate what you learn with a application context. However, it will improvement the experience a lot more if the students don't need to concern with data engineering.