Data Science Retreat: Find Top Courses & Training Locations

Data Science Retreat is a Berlin-based advanced data science program. The course consists of two months of training from industry experts, followed by a month of portfolio-centered project creation. The DSR curriculum focuses on the three disciplines that comprise data science: engineering, analytics, and business. Students are expected to have familiarity with multiple aspects of data science, Python, and machine learning before enrollment.

Data Science Retreat (DSR) is a three-month data science immersive for students in Berlin. Founded in 2013 by Jose Quesada, this in-person retreat is open to students from around the world, many of whom travel to Germany on work or tourist visas.

DSR provides advanced training, covering not only subjects like data science but also machine learning, Python, and big data. Ranked by Switchup among “Best Data Science Bootcamps” for 2021, DSR features a portfolio-centered curriculum, with small classes and expert instructors. All programs are taught in English.

Data Science Retreat is proud of its track record. Many graduates have gone on to management positions, founded companies, or been hired by corporations like Amazon, Deloitte, and Samsung. Financing options are available, including Income Share Agreements for students with EU passports.

School Locations

Data Science Retreat is held in the capital city of Berlin. Unlike much of Germany, students can get around Berlin without learning German. The city is an international tech hub, renowned like San Francisco, Paris, and London for its exciting tech scene. The majority of tech startups here use English as a primary language.

Students traveling from abroad will be pleased to learn that Berlin is also among Europe’s most affordable cities, with reasonably-priced housing and world-class cultural events. Many DSR graduates settle in Berlin after completing the retreat.

Subjects Taught at Data Science Retreat

The DSR curriculum emphasizes that data science intersects three disciplines: engineering, analytics, and business. Coursework is essentially broken down as follows.

Engineering

Data science tools - text editors & development environment setup
Programming practices - test-driven development, reproducibility, packaging
Python - Pandas, NumPy, Scikit-Learn, Matplotlib
SQL
Bash shell
Git & GitHub
Data visualization
Deploying models with Flask and Docker
Distributed machine learning with Spark

Analytics

Probability & Statistics
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

Business

Technical communication and presentation skills
Interview question practice & preparation

Use Noble Desktop's Classes Near Me tool to determine how DSR compares to other data science bootcamps. Check out data science programs here.

What Classes Are Available?

The Data Science Retreat curriculum is an advanced one, combining data science tools and programming languages like Python, Pandas, NumPy, and Matplotlib with probability and statistics, machine learning, and other analytics, business tools, and disciplines.

Perhaps more important than the details of all courses presented in the three-month retreat is that DSR is an advanced program. Before enrolling, students must have meaningful knowledge of Python, linear algebra, probability, and machine learning. The following is a guide to what enrollees should know in each area.

Students should be familiar with concepts outlined in the Python Tutorial, including variables, strings, floaters, and integers; conditionals; functions; lists; tuples, sets, and dictionaries; and reading and writing files.

Linear algebra knowledge should include the following: the differences among scalar, tensor, and matrix; element-wise matrix multiplication; and dot products. In the area of probability, students should be familiar with independent, marginal, and conditional probabilities, expectation and variance, and the Bernoulli and Gaussian distributions.

Finally, students should have the following knowledge of machine learning: familiarity with random forests and logistic regression; familiarity with bias and variance; and knowledge of the difference between test and train error. Students should also have previously implemented a machine learning project from scratch, using Pandas, Scikit-Learn, and Matplotlib.

Class Formats

All classes at the Data Science Retreat are hosted in-person. Class sizes are kept small to provide individual attention, typically 10-12 students.

DSR ensures students spend about one-third of their time on a single portfolio project. These can be shown to prospective employers if desired on Demo Day, a DSR event wherein participants present projects to Berlin’s data science community.

Nearly 250 Data Science Retreat graduates have completed innovative projects, which can be found on the DSR website.

Admissions Process

Data Science Retreat admissions begin with a 30-minute interview. Students fill out a short online application, and the follow-up interview covers experience, education, and the enrollee’s understanding of data science, Python, and machine learning. DSR typically targets a goal of around 100 graduates per year.

Pricing & Payment Options

Tuition for DSR in 2022 is €12.500, or about $14,000 if paid in advance. Students can also pay half their tuition upfront and the other half within the first two weeks of the program.

For students with EU passports, Data Science Retreat also offers a unique financing option called an Income Share Agreement, or ISA. The ISA contract requires no upfront fees, and graduates can make payments based on a percentage of their income. Check here for more information on tuition and financing.

Career Support Services

The DSR curriculum is specifically geared toward helping graduates find fulfilling work in the data science field. Each course hosts two mini-competitions, which include take-home assignments. These are comparable to a standard exercise in many companies’ hiring processes.

Career support continues with interview practice, help dialing in language on CVs, LinkedIn profiles, cover letters, and questions with expert instructors in the small classroom setting.

Alumni involvement is also a feature of Data Science Retreat. The extensive network of graduates and instructors offers a unique source of career support.

Alumni Outcomes

DSR graduates find work in various sectors, both public and private. Companies hiring graduates from DSR include Amazon, Bayer, and The New Yorker, and many go into academia.

According to Data Science Retreat founder Jose Quesada, the average time between graduation and job placement was around three to six months in 2016. This number has only improved over time, especially for students who already have several years’ job experience.

What Do Students Say?

Although there are no independent alumni outcome reports for Data Science Retreat, numerous student reviews are available online.

Switchup, which ranked DSR among “Best Data Science Bootcamps” for 2021, shows reviewers giving it an average rating of 4.77 out of 5 stars. Graduates call the DSR curriculum both “comprehensive” and “practical,” with one writing, “Job support has been amazing.”

Course Report and Career Karma both feature DSR graduate reviews, with an average rating of around 4.7 of 5 stars. Again, common adjectives include “practical,” “comprehensive,” and “wonderful.”

Not all comments are 100% positive, although even here, comments tend to run in terms like “intensive but good.” Only one student said, “the sequence of topics was not always logical,” but overall, the company gets high marks. In fact, Analytics Insight ranks DSR #3 in its “Top 10 Data Science Schools for Boosting Your Career.”

Key Takeaways

Fully in-person 3-month program
Small classes (10-12 max)
Enrollees must be thoroughly familiar with Python and machine learning
The retreat includes interview training and help designing your cover letters, CV, and LinkedIn profile
Three main areas of study are engineering, analytics, and business
Students from abroad can stay in Berlin on a tourist or work visa
Multiple financing options, including an Income Share Agreement for European students

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Data Science Retreat

School Locations

Subjects Taught at Data Science Retreat

Engineering

Analytics

Business

What Classes Are Available?

Class Formats

Admissions Process

Pricing & Payment Options

Career Support Services

Alumni Outcomes

What Do Students Say?

Key Takeaways

Top Courses at Data Science Retreat

Data Science Immersive

Subjects Taught at Data Science Retreat

Data Science

Map of Data Science Retreat Locations