Science to Data Science

This is primarily an intensive programme for working on a real-life data-science project - there is very little taught content, just some 1-2 hour seminars in the first week, and some YouTube tutorials to follow in preparation for the programme. However these are very good. The lack of taught content is why I gave 3 stars for "Curriculum" - it is not extensive, but it is good.
Don't do this programme though if you want a lot of formal grounding in programing or data-science. 

*DO* do this programme if you want to learn a wide range of very practical and broadly useful skills mostly through self-directed learning and the time/space to absolutely immerse yourself and do loads and loads of coding! 

I knew this was what the programme was about and it was exactly what I wanted. I was a lot more skilled in many areas after just 5 weeks. It would have taken several times as long to learn the same stuff as part of a job, assuming the opportunity was even there.

Unsurprisingly for a "bootcamp" you need to give this absolutely your full attention for 5 weeks. Don't plan anything else during it! And you should realistically expect to be working rather more than 40 hours a week although the choice is yours. It is entirely on-line though so the fact you're working from home makes the longer hours very manageable.

Also, be entirely prepared for the fact that you will encounter quite a range of technical problems many of which you will need to solve with very little help from others. This is both a plus and minus - I was surprised and proud of some of the stuff I actually managed to fix pretty much by myself simply because I had to. This was ultimately a good thing!

I would highly recommend S2DS - it is very good value for money indeed, and the benefits go far beyond merely learning some machine-learning and more Python (for example, fantastic careers support, fantastic access to all kinds of recommended resources, experience working with/for an actual client, working on a team-project).  Read less

 Having completed my S2DS experience, I feel so thankful that I had the opportunity to participate in the 2021 cohort. Even though the course was virtual it felt so vivid and engaging. 
From the beginning to the end, the organizers have put such a great effort to plan a hands-on experience, involving exciting real-life data science projects, and made sure that the interaction between all members of the cohort is constantly up. 
S2DS is a great opportunity for anyone looking to dive deeper into data science and obtain work experience. It is hard work all the way through 5 intense weeks but also a fantastic networking hub. S2DS allows you to manage your own project within strict timeframes, and engage with customers in discussions and negotiations. The organizers' support throughout was phenomenal; from the set up of the working systems to the technicalities within the projects.     
I highly recommend this program. Above all, I recommend enjoying it! Take this opportunity to learn from each other and also teach others. You can always ask for career advice as S2DS has people with good experience in career coaching as well. Participate actively in all meetings, discussions to be able to make the most of it. S2DS has been a great step in my data science career.   Read less

This is a wonderful course for PhD graduates in the Natural Sciences who are interested in transitioning into data science. The course was brief and tough, most of it was self-taught, which is perfectly suitable for fast learners with a PhD. The experience of communicating with the company and working in a team was especially valuable. Lots os additional technical help is provided, and there is a rich framework of talks and events that help the candidates navigate their ways into data science. I strongly recommend this course - it was a fantastic challenge and a really rewarding experience overall. Read less

Allow me to give the take home message at the start - if you are from academics and want to get working experience of data science and industry, the five weeks at S2DS are of great value.

Given that we have a great deal of technical training in our academic career, it may look like doing data science is not very different. I believe this program will change your opinion like it changed mine.

Like most of the people who joined this program, I do have a strong academic background. I have completed my PhD in Physics, and then have been working as a post-doctoral fellow. My research work mostly involves programming, data analysis and problem solving. One year back, I decided to make a transition to a career in data science, motivated by desire to solve real-world problems. I learnt machine learning, deep learning, data science by taking various courses. 

It is hard to get a data scientist job without hands-on data science experience. Looking for opportunities to gain experience of working on industrial projects, I came to know about S2DS through a friend who had joined the S2DS program and successfully transitioned to a data scientist career.

The most important skill which I Iearnt in S2DS and which is very critical in industry is communication. I closely worked in a team of 4 people, all of us from different background, academically and culturally. It was great opportunity to learn and develop the communication skills. This also gives the opportunity where we are working together almost all the time, updating each other using slack, regularly meeting through hangout. In addition to the communication within the team, we were interacting with our clients twice a week, where we used to get clarifications on the problem we were trying to solve, and constantly updating them we the progress we were achieving. Working as a consultant was a totally new and fun experience. 

The mentors at S2DS were extremely supportive. We had regular scrum meeting with S2DS technical mentors, where we got clarity on the ideas we were following and also directions to pursue in order to solve the problem. S2DS also looks into whether we are happy as a team, making sure that team remains on a cohesive ground. 

To conclude, it was really a great experience for me. I got to learn a lot, be it the hard skills or the soft skills required to a successful data scientist. I will highly recommend this program.

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Datascience is a perfect field for scientists who want to change career and transfer their STEM skills and knowhow to the IT & Data sector, but it is not always easy to find the right opportunity to kick off the transition from science to data science. The S2DS programme provides this opportunity and actually delivers more than expected: datascience projects with trading companies/institutions,  team-based work, presentation coaching, MBA microcourse, best coding practices, career advice, job fair, networking opportunities and much more. If you are looking for a data science programme think S2DS, it ticks many boxes!

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I was looking to gain some experience in Data Science and chose the S2DS programme as it offered good exposure to practical data science projects and provided the opportunity to develop the skills required to pursue a career in data science.

The programme is well structured and the mentors provide good support and help you through the difficult parts of the programme. Though there are no technical training or courses in data science, the mini-MBA helps in understanding the role of data scientists in commercial projects.

Overall, I had a very positive experience and good exposure to data science projects.

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I was involved in several data science projects before starting the program. However, these projects were limited to academic settings, often resulting in publications and proof-of-concept prototypes. These prototypes were often abandoned after publishing results in a scientific journal and rarely made it to "real-life" settings. 

S2DS gave me a good taste of a typical data science project in industry, covering requirement elicitation, model development and deployment. I had a chance to work with brilliant fellow data scientists supervised by skilled mentors, available whenever their help was needed. The 5 weeks spent in London were both intense and rewarding at the same time. The program exceeded my expectations and I am extremely satisfied with the outcomes!

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I finished my Ph.D. in October 2018. From that point to the start of S2DS, I applied for so many jobs that I have lost track. Having no commercial experience makes it very hard to find a job in a competitive market. This is why I enrolled in S2DS, as a proxy to getting real, hands-on experience in a data science environment.

What I got out of it was more than that: a circle of friends and mentors, always ready to help when I have difficulties. This, coupled with the experience, is invaluable! I highly recommend the program!

Ohh, and I got a job on the last day of S2DS!

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My background is Astrophysics and I have worked in academic research for about 10 years from my undergraduate to my almost 5-year tenure as a postdoctoral researcher. At some point during my academic career, I started considering moving into data science as I found it interesting and because there are several aspects of academia that did not fit well with my working style. Then something happened: I got selected for the Virtual S2DS bootcamp.

It has been a week since my Virtual S2DS experience ended. Do you remember the satisfaction after finishing your master degree/PhD? I am feeling the same satisfaction, with the difference though that this time it is not my own personal achievement only. Instead this time the achievement is that of a team formed by individuals (including myself) who: i) get to know each other’s skills and characters; ii) acquire new skills; iii) learn to trust each other and to work together to solve a data science challenge for a client company; iv) commit to achieve previously set up goals; v) produce deliverables for the client company, with practical and direct impact on their decision making process. The bootcamp is like an experiment concentrated into five weeks during which the key tools to be able to successfully conclude it are teamwork, communication, problem solving, time management and analytical skills (e.g., coding, machine learning, mathematical modelling, statistics and data handling and visualisation). I believe that these tools are the fundamental requirements to become a successful data scientist.

So, if a career in data science is what you are thinking about, apply for this bootcamp and enjoy the journey. You will feel motivated, interested, stimulated, taken care of and guided by the Pivigo staff members and will have a  lot of fun. Sometimes you may feel that the project you are working on is not going the way you expected/hoped to. However, it still a scientific project the one you will work on and, by definition, unexpected issues can arise. One has to be ready to face the unpredictable and solve the problems in a finite amount of time and by the given deadline. I believe that this aspect is a very important one to experience on your own skin, so that you will be ready to solve such hurdles later on during your prospective data science career within a business environment. In fact, differently from many academic environments, deadlines must me met and this aspect is a fundamental one to take into account.

Furthermore I have had the chance to meet extraordinary people from different countries, from completely different backgrounds than mine and sometimes with completely different characters. Being immersed in such a diverse environment is a great opportunity to grow into a better and more competent professional. I have made valuable colleagues and friends during this experience and I was able to learn a lot from them. I am still in touch with many of them. In addition, I have been given the chance to join a large network of data scientists, which is the perfect platform for job hunting.

Finally, Pivigo provides resources for training on many topics (e.g., machine learning, python and other programming languages, statistics, project management, business) before the starting of the bootcamp. I found this particularly useful as I had the chance to deepen and/or refresh and/or build up my knowledge on the topics needed for the project.

In a few words, I highly recommend this bootcamp and I wish you the best of luck for when you apply for it!

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I recently completed the S2DS Virtual program, and like many of the other participants I was nervous at the beginning of it all because I didn’t think I’d be able to contribute much to the project based on what I knew going in (I was also nervous because of the time difference, but maintaining London hours in Indiana wasn’t as bad as I thought it would be). There were a couple of lectures in the first two weeks about Teamwork and How to Code Well, and for the virtual program we studied various data science topics independently before the official work started, but most of what I learned in S2DS came from actually working on my project with my teammates, and it was an invaluable experience. 

 

 

I also thought that the ‘Virtual’ part of S2DS worked very well. Through Slack, Google Hangouts, daily group Zoom chats, and ‘speed networking’ with the other participants the S2DS program didn’t end up feeling very ‘virtual.’ The virtual component of the program also helped highlight the importance of communication in data science. Since all communication was done online, it was critical throughout the program to communicate ideas and results well and also to communicate openly and regularly with your teammates. I think working through a data science project with a company from start to finish online, helped us all further understand the importance of being able to explain the results of your project to people with different backgrounds and experience and also helped us improve on our communication skills. 

 

In addition to the support from my teammates, there was also a fantastic support system from Pivigo throughout the program. Both the technical mentors and the community mentor were there as resources in addition to the company mentor for the project to help us out when we had difficulties. So although a great deal of the learning and progress on the project happened individually or with my teammates, we did have several people we could ask for help. 

 

It was a fantastic feeling to have a finished project at the end of the S2DS program, that we can discuss as real data science experience in job interviews and that the company will move forward with and build upon. I truly believe that S2DS is the best way to learn data science, and more importantly learn how to be a data scientist as part of a team.

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I finished my PhD in Climate Physics in 2012 and went industry for 4 years afterwards, working for both a large corporation and startup. I signed onto the virtual S2DS course as I knew that the world is rapidly undertaking a technological shift towards Data Science and now was the time to equip myself with the skills. 

The 5 week course has not disappointed! Being paired with 3 other international people and working on a real world data science project throws you straight into the deep end of working in a fast pace and results driven environment. It is intense and challenging however the Pivigo team do provide an excellent support network of technical advisors to help you throughout the course. 

The main skills you will pick up:

• data pre-processing
• predictive modelling
• failing fast
• working in an agile environment

I would thoroughly recommend this course for anyone wanting to making the switch to Data Science, whether straight from PhD for if you have experience in industry - probably the most fun I've had at 'work' in a long time!

 

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I'm a week out of the S2DS Virtual program and after a bit more time to reflect, I still consider this an outstanding program and an excellent introduction to help transition from academics to industry.  The three main outcomes of the program, for me at least, was:

1- confidence in my abilities in Data Science,

2- an industry project with a finished product that I can point to and say "me & my team, we built this."

3- meeting a large group of talented, motivated, teamwork-focused individuals in the same situtation and with the same feelings (and not just the participants on my project!). Having kept contact with many others after the program so far, I feel a small network of likeminded individuals already growing.

 

Another main feeling I felt throughout the program was that Pivago/S2DS really cared about, and put serious effort into, ensuring everyone in the program (and the industry partners) got the most value out of it. Little of the time felt wasted, and support during all aspects of the program were fantastic.  Here's some of excellent ways they helped us

-Pre-Program Study Materials:   A long list of youtube tutorials and on-line courses to start to develop skills in machine learning, statistics, programming, teamwork, business before the course even started.

-Daily Meetings with Technical Mentors:  While my team discussed our work for the day (and yesterday's results), Technical mentors listened in and provided excellent guidance when we streered off-track.  We were fully allowed to develop ideas and approaches ourselves, and they helped by answering our questions.  Also were available for detailed meetings.  Also listened to our concerns about the project, and talked with our Industry Partner to help solidfy requirements.

-Introductory Webinars:  A few introductory webinars about the program, good-coding practices, how to be an effective team, all these helped get our teams and projects up and running super smoothly (e.g. none of us had used slack or github before, but are now experts!

-Focus on Teamwork:  coaching on teamwork skills, training having effective daily meetings (and they were very effective. I'm bringing this approach back to my post-doc group!!) bi-weekly meetings with a Teamwork Mentor who counciled us through any team/personal problems.  S2DS Staff really worked hard to keep us a well-oiled team.

-Tools for Effective Virtual Work:  I was shocked at how easy the viritual aspect of the program was.  With slack and other tools, working with the team, discussions, etc. were no more difficult than if we were in the same office.  And of course, S2DS Staff stressed we all work together :)

-Networking & Friendships:  We had evening discussion sessions with everyone in the group, we had scheduled individual discussions with each person, there was a meet-up day in London UK most of us attended.  Even though many of us didn't work on the same project, it was easy to build friendships with some, and network with many more.  A great group of people.

 

Maybe most importantly, it felt fantastic to work with a group of talented, teamwork-focused, motivated, interesting individuals all looking to learn and build together.

All around fantastic program.  S2DS Staff have clearly put so much effort into making it great, I would highly recommend to anything.

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Since I was interested in starting a new career in DS, I decided to enroll on October 2017 Virtual S2DS programme by Pivigo, and I am very happy with this experience.

S2DS is an immersive 5 weeks training that offers the opportunity to work on a real DS project for a real company with a team of aspiring data scientists. That is very helpful cause it gives a taste of what it really is a data scientist's job.

The projects are engaging as well as challenging, and put to a hard test students' analytical, critical and creative thinking skills. As for me, I learned tons of useful things by working on the project my team was assigned, primarily from my teammates.
Furthermore, the daily interaction with teammates, technical mentors and company mentors fosters the participants to improve their communication skills, which is fundamental in order to become a good data scientist.

The organization was impeccable. Pivigo mentors and all the staff were very supportive throughout the programme and help make the communication both within the team and between the team and the company mentor easier and effective.
The organisers also provided interesting panel debates with experienced data scientists as well as S2DS alumni to share their experiences and valuable advice about the transition to industry and discuss relevant DS topics.

Last but not least, the daily interaction with your teammates and other students through the online platforms used in the programme (Slack, Zoom, Hangouts) helps make new friends and start building a network of colleagues which will enrich you both personally and professionally.

To conclude, if you have a solid scientific background and are motivated to transition to data science, I can only highly recommend S2DS bootcamp!

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The programme really helps you transition from academia to data science. 

Both the technical and non-technical mentors are always available to help you with the training or post-training. The networking done during the training is really valuable. 

I would really recommend it to anyone who wants to move into data science with a scientific background, even if you are not sure if you wanna quit academia!

 

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This program is helpful in many ways. Firstly, it implemented with real-life projects from the companies interesting in Data Science, which helps the students to learn the commercial awareness in every aspect of their works. Secondly, closely working together boosted the skills to work as a team and improved many soft skills of students, i.e., communication, time management, and presentation skills. In addition, the mentors were very supportive and attentive through out the program. Thirdly, the S2DS program invited some experts and alumni who are currently working in the DS industrial to share their experience, and it was highly valuable to the students. Moreover, the daily interaction with other students in the five-week span initiated an important network for the people who want to start a new career in DS. Therefore, I highly recommend this program.

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I clearly remember that  good conversation with a very good friend of mine from the institute where I did my PhD, where he told me about a very interesting data science trainig programme he took offered by Pivigo in London. Actually, he came back to London after he finished the programme for working as a data scientist freelance in a very good project. That conversation and the fact that I had been for long time thinking about other professional paths apart from the classic academia, pushed me to enrol the S2DS 2017 programme at the campus. Since the very beginning I noticed that this experience was what actually I was looking for: the programme gave me the opportunity of explore what  data science means, not only from the theoretical point of view but, more important, from the practical point of view. The programme brought the opportunity of knowing what working as a data scientist means,
what skill are required for being good data scientist, how to interact with people and to create your own network, what you can and can't do if you want to get a data science job. All this was supported by the extraordinary work of the Pivigo people, from whom I got support before starting the course, during the course and after the course. I strongly recommend this data science programme to all the people coming from/stack at the academia that want to know how is the daily life of a data scientist and what you can do for getting into it.

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I find it hard to imagine how I would have got a job as a data scientist without attending S2DS.

The key element at the heart of the S2DS experience is the company project, and there could not be a better way to bridge the gap from “I’m an academic who can analyse data in python” to “I can tell you how to add value to your company with this data, and I know how to do it.”  Interacting with the company and technical mentors gives you the support you need to bound up the learning curve towards fully functioning data scientist.  I really enjoyed working on the project with my three team mates - we all shared a similar academic background and it was great to work with like-minded people starting their data science journey from the same point.

Another great thing about S2DS is how the program injects you into the heart of London’s data science landscape through networking events and panel debates.  This is invaluable for understanding the different sorts of companies out there looking for data scientists, and gives a big kick start to growing your data science network.

I would thoroughly recommend this course to any PhDs out there looking to make the transition to data science.

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Being a postdoc in astrophysics for now 4 years, having won a few prestigious fellowships and having publish some interesting results so far, I am on the good path to obtain a position in the near future. Plus, I really enjoy doing research, and I have the chance to be part of an amazing group. I therefore want to continue in academia, if possible. But as many of you know, even with an excellent CV, it is extremely difficult to get tenure.

To have other options in case my career in academia ends, I started looking around and to speak to some friends that went out of academia. 90% of them, mostly physicists and astrophysicists, took a job in Data Science. Most of them were excited by their new job and because I did not have time to study Data Science on the side of my work, I started to look around for an intensive training. I was able to speak to four people that did S2DS, they were all very happy with the training, so I decided to apply. Besides my friends' reviews, I was also attracted by the concept of S2DS, a little bit of theory at the beginning of the training to catch up on Data Science tools and to understand the philosophy of working in the private sector and then directly working for a company on a real project.

Two months before S2DS starts, they will ask you about which type of project you would like to do and in which type of company. A month before S2DS, you are assigned a project with teammates (2 to 3) and you have a chat with the mentor of the company you will be working for that will give you more details about the project. In my case the subject of the project was close to what I wanted.

The training starts with 1.5-ish weeks of teaching, were you learn the basics of good coding, you get some notions of marketing, economics, but you also learn some basic Data Science tools. All the classes are very general and it is not possible to get lost. As I am coding quite a lot for my work, and have 8 years of programming experience with Python (the Data Science language) I did not learn a lot during those classes, but I believe it is very good to keep everyone on track. Most of the speakers were excellent, the S2DS team is doing a great job at curating speakers.

Then you start working on the project with your teammates. The mentor of the company is there to help, but also S2DS provides you a technical mentor, specialized in Data Science, that is nearly every day on the campus. In the case of our team, the project was not clear at the beginning and was extremely challenging for newcomers in Data Science. We had to do some unsupervised Machine Learning on a big data set of unstructured texts to detect anomalies. This perhaps does not ring a bell for you if you are not into Data Science but this is probably one of the most difficult chapter of Data Science today. From what I understood, the mentor of the company was not familiar with this kind of analysis, and he could just give us a few Natural Language Processing tools available out there. He was not very organized and in the end, we did not have a lot of interaction with him. However, the technical mentor provided by S2DS helped us a lot. He was not an expert in this field either, but he was able to give us some really good advices and I believe that at the end we did a good project given the circumstances. We definitely learned plenty of very interesting tools, how to work in a team and how to move forward when you do not know where you are heading to, in a few words very similar to scientific research. I would say that this experience is rather personal, and I know that it was much better organised for other teams. I do not think that S2DS is responsible for that and it is more the company that did not do the part of its job.

During the 5 weeks, several networking events are organised, to meet the London Data Science scene, speak to former academics that transitioned to Data Science, and look for jobs. A career affair is organised at the end of the training.

Even if the project I worked on with my teammates were perhaps not the best, I learned a lot during those 5 weeks, I am confident know that I can become a Data Scientists if I want to do so, and I have learned some tools that I apply to my research now. S2DS is really a great program, very well organised, were you work a lot, but you also share very good moments with your team, other fellows. I can only strongly recommend this program if you want to switch to Data Science or even if you want to learn more about this exciting part of Statistics.

Xavier Dumusque

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Upon completing my PhD I was looking to transition in the data science field. Athough I had self-taught a number of the requisite skills that were needed in addition to scientific training I already posessed, it was very hard to gain any commercial experience. The catch-22 of needing experience to get the experience of an internship of junior position was rather frustrating.

S2DS offered a great opportunity for me to tackle a real commercial project for a multi-national company. In addition, being able to interact, ask questions and get a better understanding of what a data science role is like in a company was very useful.

The technical mentors of the course were very generous with their time and knowlegde, giving valuable insight on the soft-skills as well as the technical, helping me to understand some of the challenges when working in a business setting and having to relay information/resuts to a non-technical audience.

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It is a fantastic way to start working on a team basis and building your portfolio. Besides, you get access to extensive networking that gives you the opportunity to gain insights into different fields of the industry where Data Science techniques are applied. If you come straight out from academia, it is one of the best chances to know more about the world business. 

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