Science to Data Science
Science to Data Science offers both a 5-week data science workshop in London training analytical PhDs, and a 5-week online data science course for both PhDs and MScs. Both courses teach the skills needed to transition from a scientific background to become a successful data scientist, such as Python, R, Hadoop, SQL, and machine learning. Fellows accepted into the program will learn via hands-on projects, and work in groups to complete real-life big data problems. The curriculum also includes 30 hours of lectures on topics such as professional development and business skills, designed to help students achieve their goals after the program. For those attending the campus-based program, housing in London is included.
All applicants should have intermediate programming skills in a mainstream programming language, and a strong desire to change careers into a data science role. Applicants for the in-person class should have a PhD, or be in their final year of a PhD. Applicants for the online course need at least a MSc in an analytical science, and some programming experience.
All Science to Data Science students work on projects with real companies, and Science to Data Science will help connect students to job opportunities via networking events and membership to the Science to Data Science Alumni group.
Recent Science to Data Science Reviews: Rating 4.95
Recent Science to Data Science News
- Data Science
In PersonFull Time4 Weeks
Start Date None scheduled Cost $800 Class size 100 Location LondonThis five week workshop trains analytical PhDs and scientists in the commercial tools and techniques needed to be hired into data science roles. The aim of the workshop is to create a pipeline of high quality, commercial data science talent.
Minimum Skill Level PhD Required Placement Test No Interview Yes
- Data Science
Start Date None scheduled Cost N/A Class size N/A Location OnlineScience to Data Science is a five-week online workshop that trains analytical PhDs and MScs in the skills needed to become Data Scientists. Fellows accepted into the program will learn through practical work, and teams will work in groups to complete real-life big data problems. The curriculum also includes 30 hours of lectures on topics such as professional development and business skills. Applicants should have a PhD or MSc in an analytical science, some programming experience, and a strong desire to change careers into a data science role.
Minimum Skill Level MSc, PhD Placement Test No Interview No
Science to Data Science Reviews
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- Exactly what I was looking for!- 12/9/2019Miaomiao Yu • PhD student • Graduate • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
Science to Data Science is a great head start for anyone who has the technical and analytical skills to be a good data scientist, but lack the commercial and industrial work experience that companies look for in a candidate. The programme lasts for five weeks and involves working in a small team of three to four people on a project. The limited time meant that it was important to (1) have a good foundation in data science skills (coding language, grasp of statistics, familiarity with platforms like GitHub, etc.) and (2) manage both our and the client’s expectations on what can be delivered.
The learning curve at the start was steep: working remotely and in a team meant that communication was vital. This was quite different from my experiences in academia and learning to delegate felt awkward at the start. We also had many meetings with the company to clarify the concepts and project goals. As it turns out, one of the biggest hurdles was to understand what the client wanted, translate that into data science problems, and construct an appropriate and feasible plan that we can execute.
We did a lot of exploratory analysis on the datasets we were given for the first two weeks, and started refining our ideas by the second half of the programme. We also started working on an interaractive visualisation platform, improving on the existing data presentation method. The team dynamic varies from one team to another: we were lucky to have found what worked for us early on: splitting the project into smaller tasks and tackling them either individually or in pairs. We communicated any difficulties we faced and always operated as a team (i.e. no one was left behind/out of the loop and no one tried to 'run ahead'). With the help of our external mentor, the CEO of the company as well as the Pivigo team, we delivered products that were incredibly valuable to the company.
The programme also included web-seminars on job hunting, CVs, teamwork and panel debates from past alumni and people who work in freelance, corporations and start-ups. We also had a daily Q&A session where we discussed a topic in data science that interested us. These activities ensured that we had an all-round learning experience.
In all, the journey reaffirmed my passion for data science and was truly the best thing I could've done for my career at this stage. Highly, highly, highly recommend!
- An intense but fulfilling experience- 12/8/2019Mark • Graduate • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedInThis was a 5 week intensive data science course for people coming from academia ( MSc/PhDs). The course makes the student familiar with the way of working in on data science problems in non-academic sectors (e.g. commercial, government or charity) where the deliverables are very different to ones one might be used to in academia. Typically working in groups of 3-4 on a project assigned by a company, the course forces you to learn things quickly, whether it be new coding languages or new data analysis concepts and methods. Also you are encouraged to work to a more formal way or deligating tasks and working to targets (e.g. the SCRUM framework). This was a very steep learning curve for the first couple of weeks for someone who has been working in accademia for 10+ years. One has to abandon conceptions of learning everything about a topic or working on a project to perfection, and focus on delivering objectives efficiently and effectively. Group work is another really big focus of the course. regular communication is essential between the group members and with the company. The fact this course is virtual presents a bit of a challenge compared to a physical face-to-face interaction. However we were able to use the tools we had (zoom, skype, trello, slack) to ensure were worked together effectively. By the end of the course, we had learned a great deal, both in terms of technical and softer skills (group working, communication, remote working). The company we were assigned was very happy with our final product which was very fulfilling, in a way a academic work is not. The course also had some excellent lectures on hunting and applying for data science jobs and understanding what to expect in different sectors. I would highly recommend this course to anyone wishing to transition from academia to data science. It's a fantastic way to get experience and insight into the industry without having to make a leap in the dark.
- Debashis Sanyal • Graduate • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
I took part in S2DS Virtual 2019 that concluded in November. Although I was a bit apprehensive about the virtual format before the start of the programme, I must say that I was rather pleased with my experience at the end of S2DS. The entire cohort is divided in to teams of 4 (or 3) at the beginning and given a real problem from one of their partner companies (depending on your preference) to solve. Each team is assigned a company mentor and a technical mentor from Pivigo.
A large part of the programme hinges on effective teamwork. The team members stay connected all the time through Slack, Zoom, Hangouts, Skype, etc. We also had daily scrums in the mornings that were very useful to take stock of the situation and plan for the day. I realised that for succeeding in these kind of projects, it is important that each team member plays to their strength. The problem statement given by our client was not really well-defined, which probably mimics a real-life scenario in a company. This is where the experience during your PhD will come in handy. After numerous brainstorming and pair-programming sessions, we came up with a finished product in 5 weeks that was presented to of the full cohort, the Pivigo team, and the company mentors.
The Pivigo team organises a few webinars during the first week on good coding practices, teamwork, etc. but there are no technical presentations or teaching involved. During the course of your project, you'll have regular meetings with the client to discuss progress, and the technical mentor is always ready to help if you get stuck really bad. Apart from that, around 3-4 panel debates were organised where a number of data scientists were invited to talk about their journey and career path. There was also a daily Q&A session where the full cohort used to discuss a topic related to AI/data science, led by one participant per day. You'lI get to learn not only about different interesting topics, but also about your fellow participants. Another nice touch was the one-to-one speed-networking sessions where you get to meet each of your fellow participants. Having said that, the peer-networking is one aspect where the on-site programme clearly wins over the virtual one. I must add that all the Pivigo staff members are very helpful, and they really try to ensure that each participant is having a good experience during these 5 weeks.
Please note that this is not a traditional 'bootcamp' where you are first taught a topic and then handed out a set of exercises to test your knowledge. This is for people who are already comfortable with coding (Python/R) and have basic understanding of statistics and machine learning concepts. The rest you have pick up on the go. S2DS adds to your CV the commercial experience as a data science consultant which makes you ready to hit the job market. Another important point is that S2DS is a full-time commitment, you need to spend at least 8 hours everyday working on your team project.
Regarding job assistance, it is too early for me to comment since I've just started applying for jobs. But you do get access to the huge S2DS alumni network and the job advertisements that are announced in members-only groups. There is an informative webinar conducted towards the end of the programme that helps you structure your job search, starting from designing your résumé to negotiating your salary. Their UK network is quite strong.
Overall I'd recommend S2DS to anyone willing to transition from academia to industry as a data scientist. :)
- Remote program review- 12/2/2019Alex • Applicant • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
I participated in the Oct 2019 Virtual Programme, which invovled a 5-week project in a team of 4.
This was good experience to work on a client problem as a team and to provide business value by utilising data science and machine learning methods.
Note that this programme is for those who already have a good grasp on the fundamental data science and machine learning methods. You will be expected to apply these skills to your client's problem in a team environment.
- Working in a team. A lot of my data science work involved working alone. It is very common to work in a team in industry, so having this experience is extremely valuable. I.e. using Git, Slack, Zoom calls, etc. to communicate and share work.
- Working remotely. This is extremely good experience in itself.
- Working on a real client problem.
- Really good for CV and interviews.
- Friendly team and mentors
- Sometimes not enough support with the project (e.g. mostly have to solve client problem in your team alone)
- Too many meetings that could be seen as unnecesary.
- The virtual programme innevitably makes networking more difficult as interacting with everyone on the programme is limited.
As for job assistance, there is really good advice from industry experts and technical mentors within the programme. Perhaps some more details about the general data science interview process would be helpful. Ultimately, getting a job will be dependent on the applicant's own efforts.
For those looking for good experience and something to write in your CV. This is a good programme. Extremely helpful to be able to speak about a client project and the value that you have given to their business.
- Roberta • Graduate • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
I attended S2DS London 2019 and I absolutely loved it! Before starting, I was already sure I wanted to switch from academia to data science, and I was mostly looking for an opportunity to gain business experience before starting looking for an industry job, and to get to know other PhD students who were ready to do the same. In my opinion, there are three things that make s2ds a really great experience:
- The people. The cohort was full of international, like-minded, and very smart people, it was just very fun to be together all the time, from cooking together in the evenings to attending lectures and events. Moreover, the Pivigo team is super friendly, really helpful with anything you need, and very passionate about their jobs.
- The projects were well-thought, diverse, and really interesting! Spanning from finance to marketing to helping governamental agencies to detecting fires to recommending systems, it was really nice to get an overview of all projects during the mid-term presentations. I really enjoyed the diversity and the discussions that the presentations sparked.
- In the evenings, there were plenty of debates, talks, etc, which are a great way to get to know s2ds alumni, and, more in general, more experienced data scientist. These events were crucial for me to understand the pros and cons of moving to industry, common misconceptions about data science, and to see how quickly DS career paths evolve.
Additionally, I felt that s2ds helped my job search quite a lot. Of course I cannot know what would have happened without, but all the interviewers I talked to were really interested in the project I did (much more than in my phd work... :) ) and I could prove that I had at least a bit of feeling for the business side of projects (which is a very crucial point that many PhDs seem to underestimate..). I still got some rejections because 'you don't have enough business experience', but I think it helped in other cases (and I have a job now :)).
Hope you don't miss this chance and apply soon!
- An unforgettable experience- 11/27/2018Emanuele • Data Scientist • Graduate • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
I was already employed as a software developer when I enrolled in S2DS, I had a PhD in astrophysics and I really wanted to exploit my skills into a data science job but at that time I had no idea about what was a data science job, how to move properly into this field, how to present yourself to the market such that your experience could be considered valuable by recruiters.
S2DS helped me in all of this things. Moreover I found a lot of cool and talented people, friends who inspired me and teach me a lot. When you have to learn things on books or by yourself sometimes it can take years, but when you have the luck to make a real experince and find someone who can teach you with passion, this can boost your learning.
When I arrived at S2DS I had no claim, I knew it wasn't a magic and that I had to work hard, then we struggled a lot to finish our project in time, we suffered together, we put in it all our effort but finally we were rewarded and this is why I remember so pleasantly this bootcamp.
- Perfect Data Science Tryout- 11/21/2017Jonathan Gantner • Graduate • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
Close to finishing my PhD in Mathematics, I was undecided whether I should pursue an academic career or not. Getting a job in data science seemed a reasonable alternative, but I had no experience in the field. After some research online, I found the 2017 S2DS Training in London, which seemed the perfect occasion for trying data science in a business environment before actually taking such a job.
The application procedure was pretty straight forward - we had to send a CV and a motivational letter and then had a very short Skype interview, in which we quickly had to explain one out of three proposed statistical/machine learning concepts. (I explained the Bayes theorem.)
The classes were held in the first one-and-a-half weeks of the programme and mainly focused on Soft Skills that people from academia lack. We had lessons about teamwork, business communication, marketing, strategy, economics etc. All teachers were excellent speakers and even though the talks stayed superficial (2-4 hours are not enough to dive deeply into a subject) they communicated essential concepts. There were also a few technical classes (Introduction to R/Machine learning in Python etc.), but these classes were not sufficient to properly cover those areas. (Again 2-4 hours are not enough to cover these subjects and going through some online-tutorials is probably more effective to start learning these things.) Although several people would have preferred more technical lessons, I personally found the classes interesting and well-designed. Since the participants had very different backgrounds (from theoretical mathematics and biology to machine learning and statistics) it would have been impossible to provide technical classes that were useful for everyone.
The main part of the training however consisted in working on a project with one of the partner companies. Based on our preferences, we were divided into teams and assigned to these projects. The topics ranged from finance and marketing to health care and even applications in education. The individual experience here of course depended on the team and the company - but the general impression I got was that the teams were thoughtfully composed and most companies offered good support. A company tutor, a technical tutor and a tutor from Pivigo (the company that runs S2DS) were available for questions and assistance. My own project consisted in predicting logistical effort for a larger company and I was very happy both with my team and the supervision by the company.
Althogether I am very glad that I participated and I recommend the programme without hesitation. In particular if you want to start working as a Data Scientist in London (or Great Britain in general) it might be a huge boost for you career also because of the contacts you make as a participant - several of my former fellows found jobs there. However, I seriously recommend to study some machine learning and statistics in advance in order to get most out of it.
- Orfeas Kypris • Research Scientist • Applicant • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
I decided to enroll into the March 2017 Virtual S2DS programme, and I did not regret it! At that time I was finishing up my postdoc, and was ready to get some experience of what an industrial data science project feels like.
Pivigo split us into teams, and each team was assigned a client company, to whom we were essentially delivering a data science project, with specific deliverables. We followed the agile methodology, with frequent commits to our codebase, and regular updates and Q&A sessions with the client company.
My teammates were friendly, collaborative, keen to learn, and smart. The mentors and Pivigo staff were very supportive during the program, and mediated our conversations with the client company effectively.
Even though this was a remote programme, due to the constant communication via online tools such as Slack, Google Hangouts and others, the ride was smooth. Furthermore, Pivigo organized numerous Q&A sessions with experienced data scientists, which really helped in answering pressing questions about how to make it as a data scientist out there.
If you already have a grasp of statistics, machine learning and programming, this bootcamp will help you get practical experience working on a real-world project. Even though at times it was challenging, overall I found it very rewarding and worth the effort. highly recommend it!
- Stew Buchan • Graduate • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
When I started to plan what to do after my PhD in astrophysics, I got recommended the program by S2DS alumni. I attended the 2016 course in London and found it was a great help in boosting my confidence in my own data science abilities and working in a team. It also removed all of reservations I had about leaving academia and moving into the unknown.
I found the mentors and pivigo staff to be very valuable and supportive during the program. They were on hand all the time to help with technical support, career advice and general encouragement.
The lectures didn't increase my technical ability (online in-depth courses are better suited for this) but gave me insights into how to apply my existing skills.
Overall, I would highly recommend S2DS to anyone with existing technical skills looking to move into data science.
- Rob Spence • Astrophysics PhD Researcher • Student • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
I decided to apply for the S2DS London programme as I was heading into the final year of my Astrophysics PhD. I was starting to think about leaving academia but found myself in the position of having no commercial experience to call upon for any job applications/interviews I may have in the future. I also had no way of really knowing what it was like to work outside of academia. This worried me, and when I heard about S2DS it immediately caught my attention as a potential solution to this problem.
Prior to S2DS, I had a reasonable amount of data analysis experience under my belt from my academic studies and would class myself as fairly competent at programming in python, but I had pretty much no clue about business and no formal "data science" training whatsoever. One of my concerns before attending was that I may have been out of my depth, however it turned out I didn't need to worry. The S2DS course is well organised to suit all levels of ability (within reason!) and with a little pre-course preparation on websites such as Udemy, Coursera, Codecademy etc. you will be up to speed in no time.
The course itself is in the form of one-and-a-half-ish weeks of lectures, across different business and programming topics, followed by 3 and a bit weeks of project work with your sponsor company. I found the lectures hugely informative, and actually very engaging and interesting compared with the average academic conference. The team at Pivigo have a lot of contacts, and chose some extremely good speakers.
Within a week of starting the course, you will meet your company sponsors, technical mentors and (hopefully!) be given all the data you need for your project. (I say hopefully because for my project, due to various issues it took a little while longer than that, but it was all good problem-solving experience). Then it really is all down to you and your team from there. My project was interesting, challenging, frustrating at times but overall I found it very rewarding. I came out of this experience realising that data science was a career path I would like to pursue, and S2DS has given me a valuable network of people to get me started.
The atmosphere on the course was extremely friendly, all the attendees were fantastic, along with the Pivigo staff. People came from all over the world, from all sorts of backgrounds, whether straight from a PhD or Postdoc, or from later on in life looking for a career change. The course really is for anybody looking to transition into the field of data science. The work is intense, but there is also plenty of time allowed for socialising, both through numerous planned events as well as spontaneous activities such as movie nights, golf or a trip down the pub. Networking is strongly encouraged, and you will get plenty of time for this, both with each other and with lots of companies, many who actively recruit directly from the S2DS cohort.
I already know people who attended the course who have gone on to take jobs directly as a result of this experience, however I cannot speak for myself yet as I am still in the final stages of my PhD. What I can say is that I have received a huge amount of interest from companies and recruiters on LinkedIn since adding my S2DS experience to my profile, so this course appears to have great value as a stepping-stone into a career into data science.
To anybody reading this and considering applying to S2DS, I can highly recommend it. Be prepared for some hard work and some frustrations - of course not everything related to the projects will go completely to plan - but overall it was a hugely enjoyable and informative learning experience, one which I genuinely feel has changed my life.
- Alberto Guffanti • Senior Developer • Applicant • Course: Science to Data Science Virtual • Campus: Online • Verified via GitHub
Being still undecided whether to leave academia or not, I decided to participate in the S2DS bootcamp to get a flavour of what the life of a Data Scientist in a commercial environment would be. And all I can say is that this has been a great decision.
I opted for the S2DS Virtiual course because, due to family constraints, I would have not been able to move for 5 weeks to London, although I was a bit skeptical about the online format. I knew people who participated in S2DS London in the previous years and they all enjoyed and reccommended it, but I was not sure the Virtual course would be as engaging as the residential one.Truth is that the team at Pivigo are really great at running the course and are able to make the online course feel almost as a residential one!
The format is really good and it makes you (or at least me) realise that as a PhD/Postdoc what one is missing for a successful as a commercial Data Scientist is not technical skills but the soft skills to adapt to a different way of working.
The projects are generally quite interesting and the company mentors are very engaged and helpful and the staff at Pivigo is extremely helpful and supportive.
Being part of the S2DS Alumni community is a great way to start a professional network of data scientists and industry experts, a crucial element when looking for your first data science job outside the academic world. Although the course (and the related network) is quite UK centric, including it in your CV will boost your value in the eyes of recruiters and companies all over Europe.
In conclusion, I would definitely reccommend S2DS to anyone looking to transition from Academia to a commercial Data Science role! It will help you a lot in jump-starting your new career and, most of all, you will truly enjoy it!
- Dr- 10/28/2017Olusegun Oshota • Graduate • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
I had a previous experience as a Post-Doc in Bioinformatics and Systems Biology within the academic set-up before enrolling on the 'SCIENCE TO DATA SCIENCE VIRTUAL' . I was interested in gaining experience in the applicatrion of machine learning to 'BIG DATA'. S2DS provided me with an excellent opportunity to do just that in the sense that I had the opportunity of developing my machine learning skills on a project which involved analysis of large datasets provided by an online marketing company. Apart from the project I was able to interact meaningfully with the other would-be Data Scientists, and also gained experience of working in a remote virtual environment. I recommend the 'SCIENCE TO DATA SCIENCE VIRTUAL' to any aspiring Data Scientist who are unbale to go to S2DS in London.
- A truly great Data Science experience- 10/25/2017Pavan Sangha • Student • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
Science 2 Data Science, offered my the necessary experience to help transition from academia to industry. I have a very theoretical PhD, and i wanted a platform to show off programming and data science skills that i had aquired through self teaching. S2DS London was this perfect platform!
I got to work for 5 weeks in an intensive but fun work environment with like minded collegues who all shared the same goal. What was extremely pleasing was that i loved the project i was assigned to. I was able to work for a start up and experience the perks of working within the start up culture and at the same time work on a fraud detection problem that would have a truly massive impact on the business going forward.
If you want to be part of an amazing network, gain some experience into working on a real life data science project which not only develops your technical skills skills but also the soft skills needed to work within a team in industry, then S2DS is the place to be.
- The golden ticket to data science- 5/17/2017Naser Monsefi • Graduate • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
From the day I decided to switch from academia to data science; this course was on the top of my list. I was originally planning to do the on site course but the on-line course tunred out to be the better option (no UK visa hassles for me). The course was intense but for a good reason and it gave me a sense of how data science roles are in real commercial settings. Our team of three, had great mentors both from course side and the company providing our porject. Although I already had quite good technical skills, the course thought me a lot. My biggest achievment was how to work in collabration with others toward the same goal in a short time frame. I also learned how to look at analytical problems from a commercial view point.
In the end, beside the great experince from the course itself, I had a better understanding of what a data science do and what type of roles I would be better to apply. Eventhough they mainly help for looking jobs in the UK, by just adding the course to my CV I were asked for more interviews outside of UK and I was able to show case my performance potential in a commercial settings.
I highly recommand this course for all the academics who are planning to pursue a data analytic career.
- Best jump start for a Data Science career- 4/27/2017Matteo Guzzo • Data scientist • Graduate • Course: Science to Data Science Virtual • Campus: Online • Verified via LinkedIn
If you are in academia and wonder if data science would be a good or feasible idea for a new career (hint: it is), this is what you are looking for.
S2DS gave me the hands-on experience I needed to be confident about my potential and perspectives in data science. This is something that any MOOC or Kaggle competition would never be able to give you. I can't stress enough the importance of working in a team for a company whilst trying to solve a business problem. The value of such an experience is incommensurable, and you will take advantage of it on your CV and during job interviews.
S2DS also gives you access to a network of data scientists, career advice, and job leads, all extremely helpful for your future data science career.
All this comes in the form of quite an intense but very enjoyable 5-week experience, where you'll be in the company of very like-minded people. The opportunity to meet and discuss all sort of ideas with other participants is another invaluable perk.
I was quite suprised by how well the virtual program worked, despite having to work remotely with people from all corners of the continent. That definitely worked much better than I expected.
In short, if you are an academic looking to jump into the data science endeavour, S2DS is a no-brainer.
- S2DS is the reason I have a data science job- 3/24/2017Jonny Brooks-Bartlett • Data Scientist • Graduate • Course: Science to Data Science London • Campus: London • Verified via LinkedIn
Without a doubt the best career decision I've made. I wouldn't be in my current data scientist position without it!
The S2DS London programme was such a great experience. Although at first it can feel quite daunting, you'll quickly find out that everyone is like-minded and supportive so it never felt like a competition.
I had initially expected formal lectures on the technical aspects of data science learning about algorithms and new technologies so I was surprised when so many of the lectures were so soft skills focussed. However, through several networking events and my experience on the job market I realised just how much more useful it was to have the lectures that we did.
S2DS gave me a much broader perspective of the data science landscape and made me realise that I already had the skills to be a data scientist, I just didn't know it before. Importantly it gave me a huge data science network and the relevant commercial experience to get my data science career started.
Even after the course, the assistance and advice I received was great. No recruiter I spoke to was ever that helpful or suggested I should aim as high as the team at Pivigo. Ultimately it was a presentation that I gave about my S2DS project at a Pivigo organised Meetup that got me the job I'm in now.
If you're thinking of starting a career in data science and are not sure where to start then I whole-heartedly recommend S2DS!
- Elena Lestini • Graduate • Course: Science to Data Science London • Campus: London
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!
- A very positive experience- 10/21/2019Hameed S • Graduate • Course: Science to Data Science London • Campus: London
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.
- Fantastic experience, highly recommended!- 10/21/2019Andrius • Data Scientist • Graduate • Course: Science to Data Science London • Campus: London
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!
- A great experience; highly recommended!- 10/2/2019Shad • Freelance Data Scientist • Graduate • Course: Science to Data Science London • Campus: London
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!
- Diego Capozzi • Researcher in Astrophysics • Graduate • Course: Science to Data Science Virtual • Campus: Online
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!
- Virtual S2DS Review- 12/4/2017Laura Collins • Graduate • Course: Science to Data Science Virtual • Campus: Online
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.
- Data Scientist- 12/3/2017Chris D • Data Scientist • Graduate • Course: Science to Data Science Virtual • Campus: Online
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!
- Joshua • post-doc • Course: Science to Data Science Virtual • Campus: Online
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.
- Martino Lorusso • Graduate • Course: Science to Data Science Virtual • Campus: Online
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!