Be in Demand
Speed up your transition into data science
Advanced data science education, taught in person by industry experts
In vibrant startup metropolis Berlin, Germany
12 weeks, full-time and intensive
Most advanced Curriculum in Europe
Small class sizes (10-14)
€12,500 ( Financing option available)
All classes are taught in English
4 Jan – 30 Mar, 2021
29 Mar – 29 Jun, 2021
Data Science is such a complex topic that a single person cannot be an expert in every area. Therefore, at DSR, we have one teacher per topic. This allows for the teacher to be a master for that topic.
We source the very best experts and teachers with a track record in Data Science and Machine Learning at e.g. Deloitte, FlixBus, Zalando, HomeToGo, Amazon, New Yorker.
Data science is the intersection of engineering, analytics and business. We teach state-of-the-art Curriculum which is constantly improved every batch.
You’ll be taught by experts in the field, covering theoretical and practical uses of data science and machine learning
DANIEL VOIGT GODOY
Financial Advisory Analytics Manager, Deloitte
DR. JESÚS MARTÍNEZ-BLANCO
Senior Data Scientist, FlixBus
Senior Data Scientist, Zalando
DR. TRISTAN BEHRENS
Data Science and AI Educator, AI Guru
Data Scientist, 50Hertz Transmission GmbH
Senior Product Manager, HomeToGo
Senior Data Scientist, New Yorker
Machine Learning Scientist, Natural Vision UG
DR. PATRICK BAIER
Professor - Machine Learning, Hochschule Karlsruhe
Senior Consultant and Data Scientist, Deloitte
DR. EDITH CHOREV
Senior Data Scientist, Körber digital
Senior Data Scientist, Neuraltrain GmbH
Data Scientist and Economic Consultant, Oxera
Dr. Aline Quadros
Data Scientist, Flaconi
Full Stack Developer, FlixBus
Cloud Platform Engineer, Scout24 Group
Senior Recruiter Data & Tech, Flixbus
Data Scientist, BASF
Dr. Bastian Kubsch
Data Scientist and biophysicist with entrepreneurial experience
Principal Cofounder, StartIn-Holding GmbH
Dr. Stanislav Chekmenev
Data science is the intersection of engineering, analytics and business. Below is our teaching curriculum grouped by these three dimensions:
- Data science tools – text editors, development environment setup
- Programming practices – test driven development, reproducibility, packaging
- Python – Pandas, NumPy, Scikit-Learn, Matplotlib
- Using a Bash shell
- Git & GitHub
- Data visualisation – D3
- Deploying models with Flask and Docker
- Distributed machine learning with Spark
- Probability & Statistics
- Foundations of Machine Learning
- Practical Machine Learning
- Working with Small Samples
- Backpropagation & Deep Learning
- Computer Vision with PyTorch
- Sequential Models with TensorFlow
- Natural Language Processing (NLP)
- Unsupervised Learning
- Interpreting Machine Learning models
- Reinforcement Learning
- Technical communication and presentation skills
- Interview question practice & preparation
before the interview
There are no strict requirements on your level before the interview. Most participants have already taken their first steps learning Python or machine learning before the interview.
We recommend that anyone considering studying at Data Science Retreat to book an interview; we are happy to give advice on what you can study to get up to speed.
before the bootcamP
Below we outline the required knowledge for our participants to explore before they study with us:
For Python, we expect students to be familiar with the following concepts outlined in the Python Tutorial:
- Variables, Strings, Floats, Integers (Section 3)
- Conditionals (Section 4.1 – 4.5)
- Functions (Section 4.6, 4.7.1, 4.7.2)
- Lists (Section 3.1.3, 5.1)
- Tuples, Sets, Dictionaries (Section 5.3 – 5.5)
- Reading & Writing Files (Section 7.2)
Linear Algebra & Probability
For linear algebra, participants are expected to understand:
- the difference between a scalar, matrix & tensor
- element-wise matrix multiplication & dot products
For probability, we expect participants to be familiar with:
- independent, marginal and conditional probabilities
- expectation & variance
- the Bernoulli & Gaussian distributions
For machine learning, we expect students to have:
January 4th – March 30th, 2021
March 29th – June 29th, 2021
All students design, implement and present a hands-on portfolio project. The project is a chance to show employers your new skillset.
You won’t be alone – the Data Science Retreat staff & community will mentor you along the way.
Our goal is to get you ready for your next challenge and to set you up for success on the job market.
We help you improve your presentation and interview skills, guide you through recruitment processes starting from updating your resume to accepting an offer.
You can join our program through an income share agreement without paying in advance, and repay in instalments once you get a job after the retreat.
join our next BATCH
Toy Self Driving care (2018)
A Toy self car that drives within the borders of a circuit. Marcus Jones wrote the operating system (open source) before Amazon released theirs late 2019.
Malaria Microscope (2019)
Code runs on (donated, second hand) phones; hardware is cheap to produce (60 USD). Diagnosing malaria without needing a doctor could potentially save 600k lives per year.
The project was covered by GEO magazine March 2020.
Wheelchair path recommender
Bumpy sidewalks are a problem for wheelchair users, skaters, and small robots. This project took a gold standard of roughness driving a wheelchair around Berlin with a phone attached taking accelerometer data and video of the ground. Then the team generalized their data to the entire city using google street view. The final product could recommend the smoothest path between two points on openStreetMaps.
Self- Driving robot that picks cigarette butts
Cigarette butts are hard to pick up and a serious enviromental risk. A single butt can poison 40 liters of water. This project, inspired by the Pixar movie Wall-e, built a prototype on top of the toy self driving car from previous year. The team added a robot arm and computer vision to detect the cigarette butts. The local cleaning company liked the prototype enough to have three meetings with the team.
our participants are
PhD or Post Doc
What graduates saY
“Intense, challenging, with huge amounts of support” –Catarina
“Most productive time of my life” –Mack
Some of our graduates are now at C-level/VP positions
Chief Data Officer at Kreditech
Managing Director (CTO) at Weeve
VP Risk at Grover
CTO and founder, Mediaire, ranked the 2nd best start-up in Germany