Data Science Retreat

DSR has been one of the best decisions I've ever made. I think the opportunity for learning and personal growth is unparalleled.

The course runs with a 50:50 split between prescribed courses and a personal project of your choosing. On one hand, you get... Read More taught everything you need to know by really intelligent teachers from industry/academia. And on the other, you have the freedom to explore and enjoy a really meaningful pursuit of your choosing, while having all the support you need from DSR and it's community. This mix is unique (I think) for a bootcamp, and looking back, I wouldn't have had it any other way.

I really enjoyed learning from, and working with, the DSR Director, Adam Green. Adam is super intelligent and knowledgable about all things Data Science and Machine Learning. But more importantly, Adam is ever friendly, passionate and there to answer any possible question you may have. I am still trying to work out how he had the time to teach, organize and facilitate teachers and events, help everyone (and I mean everyone) with their projects and work on his personal projects in the interim.

More than happy to answer questions on DSR if anyone would like to reach out to an alumni.

I attended Batch 18 of Data Science Retreat from April to July 2019. DSR promised an advanced level of teaching (compared to other bootcamps) and I wasn’t disappointed. After refreshers on machine learning and Python, we dove right into deep learning,... Read More built our own neural networks and solved coding challenges. The numerous teachers all have working experience in the field and are passionate about the subjects they teach. Additionally, the new director of DSR, Adam Green, was always around and a great help in many situations. He is incredibly quick in picking up on what your problem is and giving you a pointer to the solution – an invaluable skill for a teacher. I recommend Data Science Retreat to everyone who understands the basics of Data Science and has the time and money. If you’re looking to improve your skills for the job market, you’ll learn a lot, build a network in the industry, improve your portfolio/CV, and get an idea of what it’s like to work as a data scientist.

Data Scientist Retreat provides excellent programs which combine not only the on-site teaching of real-world data science skills but also machine-learning based project building.

In my intensive three months' study, I learned in-depth knowledge of machine... Read More learning algorithms and approaches, DevOps concepts and obtained hands-on experiences in big data analytics using Spark and cloud computing. Data Science Retreat's good reputation also helped me build my data science network and collaborate with local and international data scientists. It's one of my best ways that I have invested in myself and see big returns. (Recently, I saw a new funding scheme, which is reducing the amount you need to pay up front.)

Most importantly, I met like-minded classmates and teachers at Data Scientist Retreat and really enjoyed my time with them. If I was given a second chance, I would choose to attend Data Science Retreat again.

I took part to batch 13 in 2018. I personally think that I never spent money any better. It has been an amazing experience under all points of view. Outstanding teachers and classmates. I think the overall level of the class was great. We focused on the... Read More cutting edge technologies with a hands-on approach. It has been tough in terms of intensity and hours of work but totally worthy it.

highly recommendable, really high value for money

The Data Science Retreat was for me a Career Accelerator that allowed me to acquire skills, not only in data science, but also in the tools that are related to it, such as AWS, docker, Spark and so on. It also gave me the opportunity to go through the... Read More full cycle of realising a personal project of mine, which you can see at http://www.techcontroversy.com .
This allowed me to make the move from experienced Software Developer to Machine Learning Engineer, a role that I am know fulfilling In a Berlin unicorn company.

Before DSR, I worked as a software engineer for ten years, and after finished my master in robotics, I fell in love with machine learning, so I decided to study and work in this field of science, so I studied some MOOC courses one of these courses is... Read More Machine Learning of Andrew NG, the best course in machine learning, and after that I started for looking for something like a master but with more practical side than theoretical side, and with less time, because I think studying a master is a waste of time and money, so I checked some boot camps about data science in Europe, and starting asking old alumni of these boot camps, is the money and the effort worth it to study these kinds of new masters, so DSR was the winner because most of the alumni that studied there told me a very good review about it, so I gave it a try and start studying in DSR. At the begging is not too hard to follow the teachers and make the assignment but gradually it became really hard to do it, you need to put the hours and the effort to understand the classes, doing the assignment, and to finish your portfolio project because with this project you can land a very good opportunity in the field. And I didn't regret it to quit my stable job in one of the best startups in the UK, and came to Berlin to only doing this, and don't be afraid for Berlin, all the people in Berlin understand and talk English and most of the people here are friendly, but if you believe in yourself like me, and you can handle the pressure of working really long hours, it's worth for your future. After finished DSR I had many job offers and interviews in London and Berlin, I did most of them but I didn't take any offer, because at the moment I like to work on my own business and see what happens in the positive future of AI.

Pros - great balance between taught practical, theoretical and self driven project work. Well organized and cheap compared to US bootcamps. The Berlin tech-scene provides a fantastic backdrop for DSR, with regular world class data science and machine... Read More learning meetups. Experienced and enthuastic teachers.

Cons - perhaps lacking a bit of really basic stuff - but this is picked up eventually (ie .bashrc, unix commands, Python virtualenvs). All of these are now part of my normal workflow so them not being taught doesn't mean you won't learn them, it will just take longer.

As some background, I got into Data Science after a computer error resulted in my undergraduate senior seminar being Machine Learning and Big Data for Finance and Economics at Columbia University. While having absolutely no Comp-Sci background, I voiced... Read More no protest and took the course believing "it could be fun". By the end, I was in love with Data Science and promptly decided to switch careers paths immediately.

While I loved the subject, I had profound reservations with the course itself. Its math/statistics intensive approach was alienating, and lacked conceptual explanation. Our home works were to copy code using perfectly clean datasets (spoiler alert: 90% of data science is cleaning and mining data) and left me unprepared to deal with the messy [insert profanity] that are Census datasets for my senior thesis. Finally, I felt I could talk more about the subject than actually code or solve actual problems.

My seminar molded me into a fantastic Data Science Therapist! But not a Data Scientist.

My resolve was to find a postbac that:
1) expanded upon my existing understanding of machine learning.
2) taught me how to actually solve real world case studies.

However, the intense demand for data scientists has led to the rapid birth of "for-profit bootcamps", with admission only a deposit away. Additionally, many others graduate "code monkeys" who blankly regurgitate a pre-fix menu of methods. Finally, I feared a return to formal academia would result in me becoming an expert in advanced theory with no real world practicability; another limitation of formal university programs is that data science is advancing at such a rate that a two year curriculum, especially in the years to come as the subject progresses exponentially, becomes out of date by the time of graduation.

I wanted a program that would teach me the latest techniques and how to apply them practically.

Fortunately, I found Data Science Retreat (DSR). Divinely, I was accepted to participate in Batch 08 of 2016 (seriously, as previously mentioned, had SERO programming experience prior to 2016, so bad that my comp-sci skills correctly merit 0 spelt with an S).

The approach is a unique: 6 weeks of theory and 6 of execution. You have top-tier professionals and professors from across Europe to teach you their area of expertise (Spark Pipelines, Algorithm Optimization, Pandas, NumPy, Deep Learning, etc) and you're immediately thrown into completing case studies and coding to solve realistic (or past) real world problems. Afterwards, you develop a 6 week portfolio project of your choice and present to a room full of Berlin's CTOs and Chief Data Scientists.

The program heavily relies on self-study. Nothing is spoon fed. It's overwhelming at first. Imagine finding yourself sitting next to one guy with two masters in advanced mathematics and another with a masters in computer science who used to program satellites. Across the room, two PhDs with 10 years of coding under their belts. Leading the class, a former top machine learning developer for Microsoft. As you could imagine, it was extremely intimidating at first.

Fortunately, the batch is small (8-10) and, quickly, an atmosphere of camaraderie forms and everyone helps each other develop code, solve problems, re-approach techniques, and questions assumptions. Throughout the program, as the most novice programmer, I had a wonderful network to rely on. My questions were promptly answered with resources for me to explore and learn for myself, afterwards, my solution would be checked and errors would be met with further resources for correction. As I was very passionate about my portfolio project and my ambitions as a data scientist, I strongly believe that the self study approach resulted in a much greater understanding and education.

I would strongly recommend DSR to a friend.

TIPS/HEADS UPS/SPOILERS:
* Not all teachers are created equal - DSR brings in a specialist for each item on the curriculum. Sometimes, the instructor may be a fantastic data scientist,but not a great teacher. Fortunately, you'll find your classmates confused by the same topic and a group effort to conquer it will promptly form.
*From Berlin with love - choose a portfolio project you're passionate about with techniques you'll want to explore/apply in your future career. You'll be grueling 8 hours a day for 6 weeks on it. make it count for something. Its a good idea to start thinking of one as soon as possible.
*All good things start small - DSR is continuously improving itself after each batch. Earlier reviews really don't reflect the experience of those who graduated two batches later. Expect the curriculum to improve as time progresses.
* Know how to code - learn from my mistakes. Straight up. its not impossible, but much much much much more pleasant.
*Funemployed - DSR has great job support, every student left with an interview. However, due to its Eurocentric nature, its ability to help those wishing to return to the United States is limited.

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... Read More 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 satisfied with my decision to join it. The staff, instructors, and other participants were all very helpful and in harmony.

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,... Read More 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), proper selection of participants

- 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 generally 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