WHAT IS DATA SCIENCE RETREAT?
Data Science Retreat is an advanced, three month, in person, Berlin-based data science program. The program helps professionals transition into data science. It is split between two months of teaching from industry experts and one month of project work. Data Science Retreat costs 12.5k Euro, and you can opt for paying after you find a job (no upfront cost) with an Income Share Agreement.
Data Science Retreat aims to graduate about 100 technologists a year; we expect them to go to a senior position in Europe within three years of graduation. You can find our graduates at C-level, VP, and other senior positions. You can see where our participants ended up in our graduates page. We list everyone’s LinkedIn there, and you can ask them about their experience.
HOW DO I GET ACCEPTED?
We use a 30-minute interview to decide if Data Science Retreat is right for you. The interview is a conversation where we will discuss your education and experience, as well as your understanding of Python, data science, and machine learning. You can apply for the interview.
WHAT IS THE PORTFOLIO PROJECT?
Data Science Retreat is unique in allowing participants to focus for about a third of their time on a single portfolio project. This project is a chance for participants to apply what they are taught in the first two months of the program.
WHAT IS DEMO DAY?
Data Science Retreat culminates with a public demonstration day — an opportunity for participants to present their work to the Berlin data science community. Some potential employers like to attend demo day.
IS DATA SCIENCE RETREAT FOR ME? WHAT KINDS OF PEOPLE PARTICIPATE?
Our participants tend to fall into one of four categories:
— academics — 3+ years as a post-doc or Ph.D. student.
— industry insiders — 3+ years in industry
— data analysts
— software developers
We also have brilliant graduates that don’t fit into any of these classes. The best way to find out if Data Science Retreat is for you is to schedule an interview.
ARE THERE ANY REASONS FOR ME NOT TO DO DSR?
Data Science Retreat is full time. Because many of our best teachers are working as data scientists, classes are often on the weekends.
We accept people who are employed, but the employer must give the participant the space to focus on learning data science.
Data Science Retreat is an advanced program, meaning all participants start with a working knowledge of data science. If you have never programmed, or have not had time to pick up some essential machine learning from MOOCs or books, you may be too early in your path to do DSR. You can always apply and interview if you are in doubt.
WHAT WILL I GET AT DATA SCIENCE RETREAT THAT I CAN’T GET FROM ONLINE COURSES?
Online courses are a valuable step in anyone transitioning into data science. One of the issues with online courses is knowing which one to pick. Another is that you can’t ask questions.
Data Science Retreat offers a curated teaching curriculum, which is updated regularly with the knowledge and experience of our expert teachers.
The small class sizes are an excellent format for participants to ask questions from experts. Participants find they learn a lot from other participant’s questions.
HOW IS A DSR PORTFOLIO PROJECT COMPARED TO THE CAPSTONE PROJECT FROM MOOCs?
The capstone project we’ve seen from MOOCs only walks half the path: you will be given the question to work on and the data, and all participants will work on the same set of problems.
What Data Science Retreat participants do is very different. You need to practice your creativity with data, find your question, and build a data product.
WHAT DOES A TYPICAL WEEK AT DATA SCIENCE RETREAT LOOK LIKE?
During the first two months of the program, classes run five days a week throughout the week (including weekends). Because many of our teachers are working fulltime, they can only teach on the weekends.
The last month of the program is project work — most students work on campus, others work from home.
WHAT DOES A TYPICAL DAY AT DATA SCIENCE RETREAT LOOK LIKE?
Classes run from 9:30 to 17:30, with a break for lunch. The structure of a class depends on the topic and the teacher. The ideal class with alternate between theory & practical work. Some classes are all theory — others are all practical.
WHAT ARE THE PAYMENT TERMS?
If you opt to pay upfront, you will pay 50% of the tuition fees before the retreat and the remaining 50% within two weeks from the start of the retreat.
We offer an income sharing agreement (ISA) where you can pay nothing upfront and start paying once you find a job.
An ISA is not a loan. It has multiple downside protection clauses, and it’s a good option for those who don’t have the financial situation to pay for their education. Like any other deferred payment option, you end up paying more than if you pay upfront.
See our Financing page for details.
WHAT HARDWARE DO I NEED?
Minimum requirements — Four-core CPU — 8 GB RAM — 256 GB SSD
Recommended requirements — Eight core CPU — 16 GB RAM — 512 GB SSD
A GPU can be useful for some classes but is not required. Most students will use AWS or Google Cloud for their project work.
WHAT SOFTWARE DO I NEED?
We recommend a UNIX based operating system — either macOS or Linux. Ubuntu is an ok choice.
Windows can be a challenging development environment in data science. If you insist on using Windows, you can use the Windows Subsystem for Linux to run UNIX programs.
Python is our language of choice (Python 3 — don’t use Python 2!). We recommend the Anaconda distribution of Python, which provides precompiled libraries commonly used in data science and virtual environment management.
WHAT CAREER SUPPORT DO YOU OFFER?
We know the most important thing for many participants is getting a job in data science. Our program is designed to support this goal.
One example of this is the two mini-competitions we run. These give students the ability to practice an exercise that is often used by companies in their hiring process — a take-home assignment.
We also dedicate time to practicing answering interview questions and being able to communicate clearly what data science is to non-technical colleagues.
We also offer assistance in designing your CV, cover letters & Linkedin profile.
Our network of teachers and graduates also offers an organic and unique source of job opportunities for our participants. Many of our participants are hired through these connections.
Berlin is one of the few cities that can be mentioned in the same breath as San Francisco, London & Tel Aviv when it comes to a tech scene. Berlin has a vibrant startup & meetup scene and has offices from tech giants such as Amazon, Microsoft, and Google.
Berlin has a unique and world-class cultural scene, ranging from the Pergamon museum to the infamous Berghain techno club. The city also has a rich political history, including one of John F. Kennedy’s most famous speeches.
Berlin is affordable, with reasonably priced housing and a range of international cuisines. For many of our participants, Berlin is a strong reason to come to DSR — many end up calling Berlin home.
DO I NEED TO SPEAK GERMAN?
The course’s language is English. You can get around Berlin without knowing any German, and most companies (startups) use English as their language. Berlin is very different from the rest of Germany (where you likely will need to learn German to get around).
WHAT ABOUT HOUSING IN BERLIN?
Housing is cheap! Berlin is probably the most affordable major city in Europe, perhaps in the Western world. It’s easy to find rooms in a shared apartment for $500 (EUR 450); and a studio or small flat for $726 (EUR 658/mo).
There are many resources, but you should try the woloho.com newsletter, Craigslist Berlin, WG Gesucht, and Immobilienscout. Another great resource is Toytown Germany (a forum for ex-pats). You can also try AirBnB for temporary housing while you look for something permanent.
I’M NOT A EUROPEAN CITIZEN – WHAT ARE MY VISA OPTIONS?
The options you have for a visa are specific to your country.
In general, participants either come on a three-month tourist visa or a six-month working visa.
We have helped over a hundred students with their visa process — in all cases, the sooner you start, the better.