Data Science

A good place to learn ML with solid coverage of important topics. The concepts were explained in depth and were helpful for building a strong foundation. The overall learning experience was decent and informative. However, there is still room for improvement in terms of more hands-on practice and engagement.

Overall for me it was worth it. 

Curriculum - the bootcamp begins with lectures with best practices for Python, NumPy, Pandas, Statistics etc. goes through Machine Learning Fundamentals (basics, Decision Trees, Time Series), Deep Learning (Computer Vision, NLP, Transfer Learning) and ends up with practical lectures around Debugging and Deployment. It also has useful sessions for Communications and also Job Search (in our batch both lectures were very good). 

It is a good idea to take a look at the curriculum page and what to do before the bootcamp (https://datascienceretreat.com/curriculum/). Also, if you have the chance, do an introductory course for deep learning. A good advice I got before the bootcamp "The more you do before the course, the more you will get out of it"🙂 

Teachers - some were amazing, others less so. 

The price in my opinion is high. However, one can apply for a financing program with Chancen eG. 

Feedback is asked in regular intervals and is indeed used to improve the bootcamp. It is important also to give feedback while you are attending, as it is often acted upon. 

To sum up - I met some awesome people & professionals -  teachers, organizers and fellow bootcampers - and with some of them we are still in touch. I am grateful to them for the knowledge, experience and cool things we created!

It was a good learning curve on ML for me. I learned as much from the students as from the teachers. Some students were already working on the field for several years and wanted to update and expand their knowledge. The big plus of DSR is that the teachers are bringing their working experience and expertise. So you don't only learn the perfect ML from the perfect dataset. You get out of DSR with a good professional network. 

I attended (and graduated) from the very first batch of Data Science Retreat (DSR) which took place in Berlin from the beginning of May to end of July 2014 .Since I lot of time has passed since I graduated from this bootcamp / course, I think I can now properly asses the value that DSR added to my own career. Furthermore, since I stayed in contact with the bootcamp and the students which attended several of the later batches, I think I can also judge the development of the bootcamp over time.Overall, DSR helped my own career tremendously in several ways. My salary increased significantly after graduating and finding a new job and continued to increase in the years afterwards as the skills (many acquired at DSR) were in high demand. From my experience, this was true for most graduates of my batch as well as later batches.The curriculum of the first DSR batch was very relevant for my work after graduating and DSR also helped me to prepare for finding a job and negotiating a better salary etc. Many of the skills I learned at DSR are still relevant for me nowadays. A lot of the technical skills / knowledge is out of date now, but this normal for any technical profession, especially for a relatively new discipline as data science. At the same time, I think DSR made good adjustments to its curriculum to mirror the changes taking place in the industry, e.g. switching the main programming language from R to Python.All instructors at my own batch were quite good and had relevant industry experience. Our main instructor is now the Chief Data Officer at a prominent German FinTech company. In future batches, the quality of the instructors increased even more as the bootcamp became more well known and the instructors gained experience in teaching the same material over time.As my batch was the very first batch of DSR, we witnessed some growing up pains especially regarding the organization of the bootcamp, but this improved significantly over time and several years later DSR seemed to run like a well-oiled machine.DSR also helped my career by providing an excellent opportunity to network with professionals from my and later batches, instructors and all kinds of other relevant industry people. I used my connection to people I met through DSR several times to find solution for some technical problems or further my career. People associated with DSR are - for the absolute most part - also very nice folks to know and I am glad to say I made some good friends through DSR :)Again, overall I can wholeheartedly recommend DSR for people who have a relevant background & are looking for (and are willing to learn) a lot of new skills which will help them in their future data science career.

Throughout my time at DSR, It was amazing the support I got from the teachers and Directors. It was obvious everyone was giving their best to make sure you understand accurately what they taught. The tutors were also experienced Data Scientist in the industry, which was helpful in learning the current trends in the Field.

I was in the first batch of data science retreat. I thought the course was solid and it helped me get a career in data science, and later software engineering. The atmosphere in the group was nice, and I made some friends whom I'm still in touch with. I also thought that the level and motivation of everyone was very high. The curricilum was quite intense with a balance of linear algebra and hands on data science. The teachers were passionate and mostly knowledgable. There were some session with industry people, which were interesting. So all and all I thought it was a good experience.

If what you are looking for is a hands on course on data-science, with gaining practical experience then this is the course for you. It is a full immersion course where you learn about how to solve problems using machine learning. You cover a lot of topics with great teachers.

I had a great time and learned a lot about the real world uses of ML, and recommend the course hightly. 

An excellent, comprehensive course in the fundamentals of deep learning and applied statistics that provides students with the skill and mindset that ML experts and data scientists require to address real-world problems.  DSR draws from the expertise of its diverse teachering faculty, comprised of professionals and academics who are seasoned practitioners of data science in the modern workplace.  In parallel with intensive coursework in prediction modeling, neural networks, and cloud computing through python-based coding instruction, students learn best practices and identify one problem applicable to machine learning which they work together to solve, under the guidance of instructors, by the end of the course.

Hello Everyone, 

I definitely recommend Data Science Retreat, if you are willing to step into Data Science. It is an out-of-box training program, very immersive, pushes you to your limits and offers you the different roads of data science field and you can dive into the specific field you feel excited with the support of your mentor and with the data science network you are immediately surrounded by.

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. 

Data science retreat is a unique cocktail of an advanced degree with a professional focus. Students learn from Europes top professors and professionals for theory, but unlike academia, classes focus on how to apply this knowledge and write code to solve real business case studies. After the curriculum, you're responsible for presenting a portfolio project of your choice, a fruit of self study and investigation, to a room full of Berlins CTOs and chief Data Scientists. Unlike many similar programs, the program fosters a highly individualized education, optimizing how data science could be best used by each students set of skills, rather than simply molding an armada of "code monkeys" capable of merely blankly regurgitating a pre-fix menu of algorithms or tasks. My only lamentation, through no fault of the retreat itself, is that while job assistance in Europe is increadibly strong, it's Eurocentric nature is not ideal for those returning to the US. On the other hand, its education and training are unparalleled. 

So I didn't have the patience or time to go back to uni and it was getting increasingly lonely doing online courses, and topics such as Apache Spark are simply not available in online courses. I now see why, it is quite fiddly to get it to run on your machine and so the instructors from the two sections we had on it (RDDs, dataframes and real-time/streaming) went through the set-up process. There were many great instructors in this course, again intensive training in NumPy and Pandas and some detail on the tricks within scikit-learn. The neural networks component was one thing I saw in this course for the first time, and am happy to have developed some proficiency with it. There was also Python environment management I've been dying to learn for quite a while since I damaged my system python once and had to reinstall everything. It is the proper way to do projects. There were a number of topics introduced with less detail such as big O notation and microservices which are important to know about and apply.

There were a lot of fantastic networking opportunities around DSR, with several alumni and succesful industry contacts sometimes joining for lunch or class.

I was a bit disappointed that in Germany no aspect of the course was in German and there were no German participants, but several of the instructors as well as the managing director are German. Still, it was a great group of people socially and professionally and I look forward to staying in touch.

Also, the process of converging on a project idea was more painful and less smooth than it could have been. It needs to be described in writing, it's like they think you can read their minds regarding what they are expecting. Hopefully they will fix that by the time you sign up for a course, and it is in any case a great opportunity to add something impressive to your online portfolio.

It is a very intense 3 months which was what I was looking for.

After spending 5 years in academia, I took a few MOOCs and found myself loving data science.

However, MOOCs were not giving me enough progress to becoming a data scientist. For a few weeks, I researched and applied to a few data science bootcamps worldwide. Some bootcamps focused heavily on statistics, which I found later on, are not true ML bootcamps. These are based on using statistical techniques to gain insights from data. Other bootcamps were too simple, and focused on SQL. However, I was after ML and artificial intelligence (A.I.), and that’s what I found at DSR.

Data Science Retreat covers a comprehensive, very intensive and practical training on using the most recent advances in the tools required to becoming a data scientist, machine learning engineer, and a very good understanding of big data handling (data engineering, distributed systems).

The instruction style is perfect; the instructors describe the main idea and let you struggle in finding the solution, which at the end, improves your ability to becoming independent and work on your own, being creative.

An important exercise at DSR is the portfolio project. Each participant has to come up with a product idea and implement it, which is challenging and fun. My mentor was very helpful in providing critical feedback on my deep learning project.

I have been in batch 8, which ended in December 2016. Since then, I am still in contact with DSR and they offer great support and recommendations to my job search.

Going through DSR, I am happy with my decision to join it. The staff, instructors, and other participants were all very helpful and in harmony.

What could have been done better?

- Focus more on making models for production in all the classes, such as machine learning pipelines, and enforce this through exercise from the early stages in the program.

- Provide more details on the job market for data scientists in Germany / Europe.

A refreshing experience that pushes you to explore further data science and create an ambitious portfolio project. You will undoubtly get a job at the end of the course.

During the bootcamp I personally felt the switch from learner to skilled practitioner, and it gave me great confidence in my abilities as a data scientist. I enjoyed the informal atmosphere and collaboration with my peer learners.

The pros:

- Small batches (8 to 10 participants), good selection of participants (expected strong background in ML)

- DSR covers what online courses don't cover. Assuming you come well prepared (already know python and machine learning), it will boost your skills and make you employable

- Most teachers are extremely skilled and really know their area. Some might not be able to follow though, so expect to spend hours after class to make sure you absorbed all knowledge. Teachers are available outside of class hours to answer you questions.

The cons:

- DSR claims to use the meerkat method but sometimes it sounds more like an excuse for lack of ability to teach of some of the teachers

- Still managed in a very artisanal manner, lacks consistency (e.g. teachers work independently and tend to cover the same topics, the sequence of topics is not always logical) 

- Few teachers not up to the expectations for a course of that price

Pros - 
    -  I find the screening and selection process quite intensive. So, everyone attending data science retreat are more or less in an intermediate or advanced level. So, you learn a lot from your batch mates.
    - Lecturers are experts in their respective field
    - The regularly updated syllabus me
    - Smaller batch size, in my batch it was 7
    - Attracting practising data scientists to sharpen their skills ( had a batchmate, who was working as a data scientist in a company)
    - Supportive staff, spacious place to work and discuss

Not sure pro or con-
    - Pressure to come up with data product with value for a project portfolio.  

Cons -
   - Meerkat method? am still thinking whether it was used or not

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.