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Science to Data Science

London, Online

Science to Data Science

Avg Rating:4.93 ( 48 reviews )

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 4.93

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  • Science to Data Science London

    Apply
    Data Science
    In PersonFull Time4 Weeks
    Start Date None scheduled
    Cost$800
    Class size100
    LocationLondon
    This 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.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelPhD Required
    Placement TestNo
    InterviewYes
  • Science to Data Science Virtual

    Apply
    Data Science
    In Person
    Start Date None scheduled
    CostN/A
    Class sizeN/A
    LocationOnline
    Science 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. 
    Financing
    Deposit£800
    Getting in
    Minimum Skill LevelMSc, PhD
    Placement TestNo
    InterviewNo
  • Laura Collins • Graduate
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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.

     
  • Data Scientist
    - 12/3/2017
    Chris D • Data Scientist • Graduate
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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!

     

  • Joshua • post-doc
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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.

  • Martino Lorusso • Graduate
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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!

  • Ana • Graduate
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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!

     

  • TC Peng
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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.

  • Alejandro Zamora Soto
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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.

  • Ross Williams • Data scientist • Graduate
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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.

  • Xavier Dumusque • Dr. • Graduate
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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

  • Jack • Graduate
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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.

  • Dr
    - 10/28/2017
    PhD in Physics, Computational material Science, Web app Developer and Data Scientist • Data Scientist • Graduate
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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. 

  • Guido Franchetti • Graduate
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    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.