Science to Data Science

S2DS provides is a very useful if compressed immersion into the data science world. About 2 of the 5 weeks of the project are mostly devoted to lectures of various kinds. While, given the time constraint, these cannot be expected to go into great depth, they are still useful to get an overview of various subjects, and of some of the existing tools. The core of the bootcamp consists in teamwork (3-5 people) on a "real" project provided by one of their sponsors. The project quality can vary a bit depending on the sponsor - I was very happy with mine. This is in my opinion the most useful part of the experience, as it gives an idea of what a data scientist job consits of, at least in a particular sector. The Pivigo team and host of mentors are always very friendly and available and for support. Being surrounded by about 100 people of various nationalities and backgrounds and with a similar interest is also very enjoyable. There are considerable opportunities for networking.

 

 

I had several years of experience as a Post-Doc and knew the academic job-landscape well, but when I decided to venture forth I realised that I really didn't know anything about how industry operates, nor how to sell my skills.

S2DS was hugely transformative in this, as the curriculum and applied project are designed to give you an understanding and experience of working in companies. I was impressed with the support network Pivigo put in place for the course: we had solid mentoring from the company we worked with, excellent advice from external technical mentors and dedicated Pivigo mentors who helped with the organisation and communication within teams. I feel I learned more about how to organise a fertile work environment in those 5 weeks than in some year-long projects I can think about...

On the technical skills side, would say that this is not the main brief of the course, and applicants should come with a good grounding in place. The suggestion for preparatory online courses were helpful for that.

Doing the course has equipped me with knowledge of how to market my skills and what to expect out there. Having tangible commercial experience has meant that potential employers and recruiters now have a completely different attitude to me than before S2DS.

After the program I quickly got into conversation with one of the companies and I'm about to sign my first employment contract outside academia with them. Pivigo continued to mentor me throughout this process.

So in conclusion, S2DS delivered exactly what it says and has worked for me! Plus, it's a lovely environment with great people. 

 

I had been waiting to move into Data Science from Academia for over a year and S2DS gave me the start I needed. I couldn't wait for the live corse so did the virtual one and recommend it if you are in the same position. You have to be motivated but the instrutors on the course do their very best to help with multiple checkins and are always on hand to give advise. I got to meet every person on the course with arranged one-to-one chats so I didn't feel like I was doing this alone. 

After the course I used the project I did and what I learnt from it in interviews to help me get a job. It gace the interviewers something to ask about and me something to talk about to show I understood not only data science but industry. And when it came to getting a second job, I went through the S2DS alumni groups and got a fantastic job thorugh their carrers area. 

Definitely worth the effort and time to take this program if you are interested in a carrer in data science. It's a great gateway in. 

I would recommend S2DS to any scientist interested in a transition to the data science industry. As other reviewers said, the skills are already there, but it's difficult to break through in the industry with only academic positions in the CV and without knowing anyone. S2DS fills both of that gaps, giving the vital commercial experience that is nowadays needed also for entry job levels, and a network to be able to put your foot in the door.
There is a huge variety of companies at the program, and most of them are hiring (and not only the people doing a project for them, I'm proof of that!). The project will give you something interesting to talk about in any interview you will have to do, while the Pivigo recruiters will help with your CVs and applications. I've got positive experiences with very few recruiters, and David at Pivigo is one of them.

Only downside, if I have to find one: the program is very UK (particularly London) oriented, so if you want a job somewhere else, the network will be less useful. But, again, I found a job in Paris through the Pivigo network, so staying in London is not an obligation.

The 2014 S2DS London summer school provided me with the perfect support and opportunities to transition to data science after leaving astrophysics. I wasn't sure exactly what I wanted to do, but the 'try-before-you-buy' approach allowed me to test out the business world for a month before making my final decision - I loved the company I did my internship with and they wanted to hire me, so I've been happily working there for 2.5yrs now.

The course itself was excellent and included a mix of training material and hands on project experience. It's 5 weeks of very hard work, but totally worth it, and the most energised I'd felt towards project work for a long time.

Besides the data science and business skills/training that the course includes, it also provides you with a ready made social/business network. Many of us have jobs in London and still meet up regularly. 

In summary, highly reccomend it for anyone looking to move from academia to data science. 

 

 

Before finding out about S2DS I had already decided that I wanted to move into data science, so before applying I had been working my way through a few online courses, as a way to get a broader understanding of the skills needed in data science. And worked on a couple of personal projects based on public datasets, just to get a feel for using some of the tools and an understanding of what public datasets look like. On the programme there was a good mix of people with different skill sets, which was helpful when getting stuck with a problem, as there was someone who was able to give me an idea of how to fix it or another way of looking at it.

I was one of the people that took part in the very first virtual programme, meaning it was a new experience for all involved, so there was no set rules about the way to work, we had to experiment and find what worked best for us. The way they do things now may have changed slightly, as they refined the programme, but the main way of working (conference video calls with all members and group skype sessions) should be the same. The members of my team were only a short distance from London (purely by chance), but all the other teams had their members spread all across Europe.

Doing the virtual programme didn't hinder my learning experience, because a lot of the learning involved going off and exploring how to do something. Then afterwards reporting back to the team, by sharing links to examples, useful info or some graphs that you had produced. And if we needed to talk, we just started a skype call or google hangout. I had done remote working as part of my PhD, so was happy with the idea of it, and I had been thinking about doing a data science programme for a while and when I saw the first S2DS virtual advertised in their newsletter, I was very keen to give it a try.

I was happy I gave the programme a try, as it gave me a better understanding of the business side of data science and helped me make a number of useful contacts. And I notice that after putting S2DS on my CV, I was getting through to more job interviews and it was something that a number of interviewers were interested in talking about. So it was helpful as a real world example, that I could use to explain how I had tackled challenges, met key goals and interesting facts I found out. And the people from S2DS continue to be very helpful after the programme, with advice and informing me about job events.

I am really grateful that I had an opportunity to be part of this five-week data boot camp. I especially appreciated that it is tailored for people from academia who want to shift to data science. In this way I could meet other people in similar situations as mine, which was really helpful. Five weeks might seem short, but the program is so well organized that you learn many things during the short time. Probably the best thing is that you participate in a real-life data science project with a company. While working on this project, you can learn so many things, including (but not limited to) technical skills like GitHub or anything connected to coding and machine learning, using different tools working in a team, communicating with your team and with the client, regularly presenting your work in a clear manner, working in a fast-paced environment... I would be happy to recommend this school to anyone who is seriously considering switching from academia to data science.

 Dataknowledge Science may be a combination or mixture of mathematical and technical talent, which can need business vision additionally. These skills area unit won’t to predict the long run trend and analyzing the info.  Data science is a "concept to unify statistics, data analysis, machine learning, and their related methods" in order to "understand and analyze actual phenomena" with data. A data product is a technical asset that utilizes data as input, and processes that data to return algorithmically-generated results. For more Information please visit our website  https://www.gologica.com/course/data-science/ 

Pros:
During this program I worked in a team of four with a company in a commercial DS project.

It is a very intensive program with very interesting webminars, panel discussions and tecnhical support from internal and company mentors.
At the beginning I was reluctant about how to work remotely in this kind of projects (as I have done all learning/projects by my own in the past), but the countinuous meetings with the team and mentors made the communication and team work being a success.
Also, I tried something called 'pair-programming' that, at first, sounded like a very difficult thing to do when people are not sitting together, but after the experience, I am planning to add it to my way of working( it is a great way of moving fast in the project at the same time of learning from others).
Another thing to highlight is that S2DS community is great! Lots of activities are organised every week to know each other as we worked remotely and there was even a 'Day out' in London that was excellent!

I would recommend this course, without hesitation, to anyone struggling to move into data science or who wants to find out what it’s like to work as a data scientist.

I took part in the S2DS Virtual Program in October 2019 while based in Germany. The application process consists of an online application on the Pivigo website, followed by an interview which tests basic technical knowledge as well as asking general motivational questions. About 3 weeks before the program we were given access to several program-specific videos covering things such as programming in Python and R, data visualisation and git. The videos are very clear and great to get started with any topic you are unfamiliar with. Also provided is a document suggesting additional learning resources as well as interview preparation materials.

On starting the program there are several introductory talks for the first two or three days; however, the majority of the program (which lasts 5 weeks) consists of working on a real data science project from start to finish with a client. My team was working on an interesting project with the UK Food Standards Agency (FSA). On assigning projects, individual preferences are taken into account. The virtual format of the program works extremely well and is of great benefit, especially with regards to changes in working habits in recent times. The majority of the teams made use of Slack, Github, Zoom and Trello for communication and team organisation. The team is generally left to its own devices; however, regular meetings are organised with a company mentor (in our case from the FSA) and technical mentors from Pivigo to keep the team on track. Another nice touch is regular individual meetings with a personal mentor at Pivigo, where additional more private matters can be discussed. 

Aside from the project, virtual networking sessions as well as Q&A sessions are organised to get to know the whole cohort. These sessions are not only great for practicing networking skills but also make you realise that everybody is in the same situation. A series of panel debates are also organised regularly with data scientists from startups, corporations and former S2DS alumni. These are very informative and give a good overview of the breadth and depth of roles available in the world of data science as well as allowing you to ask any questions to the panel.

A very helpful careers presentation was also given towards the end of the program, which really made me think about changing my approach to the job search.  Immediately following the program individual CV and Linked In profile reviews can be requested at any time. You are also given access to the whole Pivigo S2DS alumni network (over 600). This is useful not only for access to privately shared job roles, but also as a knowledge resource for any technical challenges faced later in your career.

At the end of the program final team presentations are given in the form of a webinar in additional to the requirement of a written report for the client. Not only was there a great sense of achievement on completing the program but a real sense of community with the cohort. The program was an extremely useful topic in a recent interview I had: here the journey of doing a project from start to finish offered by S2DS was key. The interviewers were also impressed by how so much was achieved in just the space of 5 weeks. 

I can wholeheartedly recommend the program to anybody interested in a career in data science. I would emphasise that for an academic thinking of moving into industry (like me), the experience is invaluable even if you do not end up pursuing a pure data science role as a lot of the things learnt here are transferrable to many related technical roles.

Let me begin by stating that I applied for S2DS,  but was not accepted. The people that I interacted with during the process seemed to know what they were doing, so I will assume that they were right in rejecting me. If I do not fit in the group or am not fit to be a data scientist, I can only agree with their decision not to waste a valuable spot on me. What I do not agree with is the way that information on my rejection was provided to me. 

In April 2018 I applied for S2DS London. The programme looked great and I was very enthousiastic and eager to join, as I was at the end of my neuroscience PhD and was thinking of a career in data science. I was invited for an interview and had a pleasant (but definitely not flawless) conversation with the woman on the other side of the skype connection. I was given her e-mail address for any further questions and I was told that I would receive information on acceptance by April 30th latest.

Being very eager and nervous whether I would get accepted, I barely made it until May 1st before I couldn't take the excitement any more and I e-mailed the person I had my interview with. I never got a reply from her. Two days later, I decided to e-mail the person that had invited me to the interview. She finally replied a week after the self-applied deadline of May 1st with the information that they were very busy accepting people and would get back to me soon. 

Two weeks later (May 21st), I still very much wanted to join and decided to be the one to open the conversation again. I got the reply that I was not immediately accepted, but rather placed on a waiting list with the information: "There are always a few who decline their places or drop out and then I would like to be able to make you an offer". I thanked her for the place on the waiting list and decided that all I could do was wait and I did. About three weeks before the course was supposed to start, I decided to let them know that I would still be very happy to accept any open spots in the course. I never heard from them again.

 

Sorry for the long post. In summary, I assume the course is great and very worth taking. However, the rejection procedure is not very professional and may leave you with a slightly bitter taste, given the time you probably invested. 

This course is a great way to get soaked in the world of data science. It provides a great overview of the data science scene, at least the English one, and offers great opportunities to start your career.

The training is not a course where you learn to program, that should be had beforehand. This is a training where you learn a few new tools and methods, but the most valuable part of the training, besides the project experience, is the business talks they offer, they give a great introductions to understanding the motivations of the science you do in industry. Having the experience in a company (of course this depends on the size of the company) is by far the best thing of the course, since you get to see how things move "out there".