Cambridge Spark Ltd

I was one of the first people to do the Applied Data Science remote learning course in 2018. I have done my own self-directed learning online on data science and Python but this course really offered me the structure I needed to learn good practice in... Read More the industry and do hands-on learning. I moved into a data scientist role by the end of the course and the course has given me a solid foundation in a variety of data science topics.

The main things that attracted me to the remote learning course were: i) the ability to do a structured curriculum at my own pace (c. 8 hours a week) rather than attend bootcamps at the weekends; ii) good value offered by the remote learning option; iii) ability to get feedback on assignments; iv) curriculum seemed more rigorous and industry-focused compared to other providers.

I'd certainly recommend the course. On those four aspects above, my expectations were surpassed. However people who do remote learning need a good level of self-motivation and discipline in order to get the most out of it. I would have struggled to juggle a 6-month in-person bootcamp with a full-time job so the remote learning option was ideal for me.

Pros:
• Same course content as the in-person bootcamp. If you care more about course content than things like networking, then the remote option offers great value for money.
• A great range of tutors drawn from industry and academia deliver the course materials in recordings.
• Rigorous course content and covers the latest developments in topics. Advanced topics you wouldn't see in similar courses include some of the ensemble methods, material on NLP and tools for interpreting black-box algos. For one example on the cutting edge, it was great to play around with SHAP little more than a year after Scott Lundberg's paper on the framework.
• A lot of material is given in the course - plenty of breadth - so I'll have great reference material on the topics I encounter less frequently. No wonder people who do the in-person bootcamp find the amount of content quite intense. The recommendation for the remote learning course is to do around 8 hours per week, but to have more than a deeper understanding of some topics you may want to spend more time than that.
• Assignments are challenging and generally fun to do. The automated feedback from K.A.T.E. usually gives you an idea of how to make your code more robust, e.g. to edge cases you hadn't considered in your original code. That's test-driven development in action right there.
• The Spark community and people on the team are very friendly. I've met alumni and the team at conferences and other events after the course. On the community / network side, I think this will become very strong in the coming years. The Spark team seem keen to cultivate that.

Cons:
• As a remote learner, I think comms during the course could be much better. It was fairly sporadic between course modules and in the run-up to the Capstone project. I think comms help people to feel like they're on the right track. I also wasn't asked for feedback after completing modules - there are a few that could be tweaked to work better for remote learning (e.g. the flipchart / whiteboard heavy lectures could be difficult to follow).
• The Slack workspace is on the free pricing so messages older than around 6 months disappear. Students will have similar questions to ones people had a year ago - if Slack gets upgraded it would help things be more 'self serve'.

The remote learning course doesn't seem to be offered any more but I think the Applied Data Science curriculum is excellent. I have met people who do the bootcamp and they have found it rewarding.

I came to Cambridge Spark after tried an online course but failed. I realized that I need a face-to-face learning experience which will allow me to ask questions simultaneously. I was very struggling on the Cambridge Spark course because it was definitely... Read More very technical, and the speed was fast and it covered fast range of Data Scientist topics. I had a technical background in my academic degrees but in my past jobs I used very little of them so this course definitely stretched my brain. Needless to say having to look after 2 young kids adds extra hard work on top. I had to be very discipline and prioritized things over a period of 7 months. It was like doing a degree with the amount of commitment and money spent on this course. But I was very glad that I did this course with Cambridge Sparks. It was a very comprehensive course which covered all aspect of DS. Yes it was very fast so it required candidates to read/study a lot in advance. Otherwise you will definitely loss in the class. Pro: The content was very technical and the lecturers with all different backgrounds specialised in the particular topics they are teaching. They were extremely helpful and very patient to answer questions. There were also teaching assistant in each class to help out. The KATE system works very well. I learned a lot from just working on it myself. Con: Some lecturers were brilliant in terms of explaining things, some are not. They definitely have lots of knowledge in their fields, but I guess it does not mean they are all very good at teaching. I want to point out that, among all the very helpful lecturers such as R, K, D, there are two female lecturers Cambridge Spark have were extremely good at explaining things even on the very hard topics. Overall, I was very pleased that I invested my saving and time on courses with Cambridge Spark! I am still looking for jobs so hopefully soon I will land with one. But I am confident that I will be able to find something in DS field.

I originally saw the Cambridge Spark course via an advert on social media and was hugely sceptical until I met the organisers at PyData 2018. I had been shopping around for a course to upgrade my stats and programming knowledge I had from a science degree... Read More I did a while ago. I considered some of the other bootcamp providers in London but I was really concerned about the quality of their teaching, they seemed to teach data science like it was front end or full-stack development.

The main factor which makes Cambridge Spark stand out is the quality of their teaching staff. They have a variety of PhD, postdoc and industry staff who were almost never caught out by the questions which people had, it was clear they all really knew their stuff and could communicate this. I did not get this warm fuzzy feeling when I looked at some of the other bootcamp providers. As a Biologist turned data scientist, I have learnt a huge amount of coding 'good practice'(PEP8, unit tests, code quality), which I had previously paid lip service to but now gives me an edge at work compared to some of the purer data scientists. I also keep bumping into Cambridge Spark alumni working in interesting and challenging data science roles all over the place.

Pros
KATE - their automated marking system is fab, it has taught me so much about coding and the ability to get instant feedback is phenomenal.
Jobs - I wasn't looking to move jobs but I saw a number of my peers transition into good data science jobs due to the course.
Teachers - Raoul, Kevin and the team are awesome teachers, who you will learn a lot from.

Cons:
You cant learn Hadoop or Spark in a weekend or two, so this is more like an orientation or primer so that you know where to get started.
Our cohort size was quite large and there was some wastage, I think they have reduced the cohort sizes now.
This is hard work, you are in lectures every other weekend and then spending the next weekend doing the homework. If you are in a full time job, this is really draining.

Thanks to the whole Cambridge Spark team for an amazing learning experience. It was quite bitter-sweet when I finished. Great to get my weekends back but sad to no longer see my peers or the staff.

I did the certification in 2018 in classrooms during the weekends (not the online version)

Cambridge Spark Applied Data Science certification is a very solid certification covering all the key topics in data science. If you don't have any CS background,... Read More you will have to study some foundations several months prior to the beginning.

You will learn a lot in a relatively short period of time. Obviously be ready to work hard but the experience is very rewarding.

The team has a good mix of PhD researchers and professional data scientists, therefore the modules provide solid theoritical foundation while being hands-on. In addition, it was very interesting to meet students with very different backgrounds.

This bootcamp really changed my way in looking at data and technology and helped me a lot to move my career into data analytics.

I would advise anyone who is willing to move into data science to attend this data camp.

I decided to take part in the Bootcamp After struggling with online courses, I was keen to train in-person and receive expert feedback. The calibre of instructors, coming from top universities and industry, was incredible. Each module was led by the chosen... Read More expert for that subject from among the Cambridge Spark team. The course runs over alternate weekends in central London, which was a big factor as I couldn’t commit to full time.

I liked the community that formed amongst both the students and instructors. It’s a cutting-edge industry and no one has all the answers or knows which direction things will take. It was great fun to explore new tools and be exposed to so many ideas and potential opportunity by people who love sharing what they do.

I’ve been impressed by the friendliness, enthusiasm and expertise of the staff and instructors. They’ve created an open and inclusive culture, which is conducive to learning, whatever level you’re at. The experience was definitely worth it and one I will harness.

I studied with Cambridge Spark for a year on the online applied data science bootcamp. The quality and breadth of topics covered was excellent as was the online community and support throughout the course from the tutors.

The course is fast paced and will... Read More require a sizeable commitment of time to complete but 100% arms you with the knowledge and expertise to be able to tackle industry data science problems. It is now a regular occurrence for me seeing topics in industry and at work coming up that were covered in the course.

The capstone project at the end is what sets the course apart from other competitors (I had previously studied data science topics with other online education companies such as Udemy/Udacity to name a few). I got the opportunity to work with a start up on a computer vision problem using some of the deep learning techniques taught. This has proved invaluable for my confidence and ability to showcase the data science skills that I have built up.

Would highly recommend the course for anyone thinking of applying and attending, as I said it is intensive and will require a significant time investment (10+ hours per week) but is ultimately worth as it arms you with industry ready skills for data science.

Cambridge Spark is an amazing collection of knowledgeable people that will help you start your journey. I really enjoyed the overall informal setting. The syllabus is extensive but is made very clear during the lectures. Most of all, I enjoyed K.A.T.E.... Read More which essentially gives you instant feedback when you submit work. This accelerated my momentum as I did not have to wait on a traditional feedback process.

The Bootcamp is hands-on which makes your learning very efficient. I prefer this to traditional courses where there is lots of theory that can never be leveraged.

Overall, I was very happy with the Bootcamp as Cambridge Spark equipped me with the foundations that I need to perform advanced analytics, this ultimately led to a promotion into a role that I really enjoy.

My overall experience with Cambridge Spark was very positive. I liked the challenges which were constantly there, dedication of the teachers and organisers as well as practicality of the course. Although the course required a lot of hard work, I was very... Read More happy with everything I learnt and as a result, managed to find a new job as a Data Scientist.

Before Bootcamp I had been working as Business Intelligence Analyst for four years. At the beginning of my career I was impressed by BI tools which allow you to build the dashboard so easily - you just need to drag and drop and you have a beautiful summary... Read More of your data in few minutes. After a while, I just realised that really often I am frustrated because I was not allowed to put the legend on the bottom of the graph because the BI tool I used have only two options - top and left. I decided to learn how to code to create the visualisation the way I want. I started few online courses but unfortunately, it wasn't enough. Really often I got stuck with the code or with the concept.

During Data Science Festival, I heard about Cambridge Spark. I checked their website and I found information about the first edition of Data Science Bootcamp. I had a call with Raoul to discuss what I expect from the course, if it fits my needs etc. After 20-minute talk I was convinced and I signed up. I think it was one of the best decision of my life. In 8 months, I learnt a lot and what is more, I found a job as a data scientist.

What I get from the bootcamp:
* Understanding the whole data science lifecycle
* Confidence with using Python for data cleaning, data visualisation, feature engineering, feature selection, machine learning algorithms etc.
* Understanding machine learning algorithms. I got a solid knowledge which allows me to understand more complex algorithms.
* A lot of help with understanding difficult topics and also a lot of patience to explains some concepts again and again.
* Knowledge how to use git (Before I don’t remember how many evenings I was crying because I didn’t know how to solve merge conflicts.)
* New contacts and the ability to work with people from different backgrounds (software developers, data engineers, economists, data analysts, data scientists, PhD students).
* Real experience. During final project, I was working on the solution for one of the British companies.
* Presenting skills (presenting the homework and also the final project presentation).

I did the Applied Data Science Course with Cambridge Spark from September 2017 to April 2018. I was part of the first cohort to do the training and far from feeling like a guinea pig, I thought that the program was really mature, even though it was the... Read More first iteration. I think some of the modules have been switched around slightly since then to help with the flow of the material, which should make the course even better.

I thought the topics were relevant to data science jobs in general, although there are topics at the edges such as survival analysis (useful for roles in ecommerce) which weren't covered but then I thought were quite easy to learn with the Python I had learned on the course.

On of the best aspects for me were the networking drinks and dinners where we met with data scientists and even startup CTOs from industry. I also really enjoyed working on the keystone project, getting access to a data set I would have never been able to work with otherwise.

When I think about what to improve, it would probably be adding a voluntary 'git-day' somewhere along the line - it took me a long time to really get used to git command line and all the magic it does. Other than that I really enjoyed my experience! Thanks guys!