How to Become a Data Scientist (with no Programming Experience)

Copy of Copy of Copy of Copy of Copy of Copy of Copy of Copy of find a waynot an excuse 5

Tell us a little bit about your current role and background

My background is in economics and business. I currently work as an impact and evaluation manager for a non-profit organisation. My field is in research and development, producing insights for strategic purposes, and for projects, to inform decision-making in general.

That sounds really interesting, so what was it that made you want to study Data Science?

A couple of years ago I was doing my masters in London, and part of it was an entrepreneurship programme. My friend and I were working on a tech start-up idea, and since we didn’t come from a tech background, we had a few challenges building up the concept in general, and obtaining funding.

Most importantly, this where my interest came from. I was generally interested in the tech world, and generating interesting solutions related to international development, business, and finding solutions for the tech sector. Since then I’ve been looking at ways to apply Data Science to my role and to follow my own interest in founding my own tech business.

Since then I’ve been looking at ways to apply Data Science to my role and to follow my own interest in founding my own tech business.

When I was looking at somewhere to start, I looked at various areas to see what would be the best way. The idea of doing a bootcamp was really interesting because, first of all, I felt like the use of data and Data Science techniques in general — and all the cool things we would learn — would either help me improve my performance in my current job by enabling me to produce better insights, and not just rely on excel and SPSS, and make these insights more attractive. 

I felt it would also give me a way to enter the field and explore further what kind of potential I have there, and where it could take me.

 

Why did you choose to undertake the Python Bootcamp with Cambridge Spark?

There are so many choices, especially for someone who is trying to find a way to learn Python/Data Science. 

I liked the idea the course enabled me to develop a good foundation in two weekends without conflicting with my full-time job.

It was confusing where to start and how to do this. So I’ve read that Python is one of the general and accessible languages (in comparison to others) to learn and really get into it. But also I wanted to get into the Applied Data Science Bootcamp with Cambridge Spark. I wasn’t 100% sure that I could do this as a person who is coming from a non-programming experience whatsoever and I liked the idea the course enabled me to develop a good foundation in two weekends without conflicting with my full-time job. 

For me, learning Python definitely seemed like something me and many others could benefit from, and the bootcamp enabled me to have a taste of what was to come at the Applied Data Science Bootcamp.

 

What was your experience of Python Bootcamp?

It was a really positively challenging and enjoyable experience overall. It was one of those things where I haven’t been outside my comfort zone of learning something for a while and so it was a good way to do this. Those things could either go really good or really bad, luckily in my case it was challenging, in a good way.

I found the Teaching Fellows to be very supportive, happy to answer questions and make sure that everyone is happy.

There is definitely still a lot to be done, in terms of developing myself. The Teaching Fellows covered a lot on the two weekends. For me it’s still a learning curve, I still need to practice, and to work on my skills.

I found the Teaching Fellows to be very supportive, happy to answer questions and make sure that everyone is happy. They even stayed longer with us on the last day to recap everything and cover any gaps which was really helpful.

Across the two weekends, there was attention to maintaining an open channel with students, the Teaching Fellows were very responsive to emails, answering questions and asking for feedback and ways to improve the bootcamp. You can really see that the [Cambridge Spark] team are passionate about what they do, and for me, that was one of the many things that kept me interested and curious to learn more.’

The group of people I studied alongside with were also very cool. It was great meeting and networking with new people, coming from different backgrounds, and exchanging experiences. I received some other recommendations for Applied Data Science programme, so I’ve decided to go for it!

 

What was your experience of using K.A.T.E.®?

As a software, It’s really accessible to work with.

During the second weekend, the tutors spent some time with us to go through it and how it works. I liked that you could actually have the ability to go back and improve your feedback. I’m used to learning in a traditional classroom-type scene, and this isn’t like that which is nice.

 

What would you say were your favourite parts of the bootcamp?

The most enjoyable part was the ability to challenge myself positively, but also to learn from all of the expertise we had in the room. I particularly liked that there is a lot to explore in the field and to learn that Data Science isn’t just reserved for those traditional types with a Ph.D., or from a programming background. I feel like if I dedicated enough time to learning, I could find my place in the field.

I really enjoyed the structure of the training and learning from the different experiences and the examples they presented to us.

I’m at a point where I’m trying to explore my career options and progress so that was a core thing. I wanted something to give me the security that this is a good decision and to just go ahead and do it, which is why I decided to sign up for the Applied Data Science Bootcamp after the Python Bootcamp too.

I really enjoyed the structure of the training and learning from the different experiences and the examples they presented to us. Sharing all these things, it just gave me this confidence. As for topics, I would definitely say my favourite topics were learning the foundations of functional programming and things that were really core, and the object-oriented topic. The trainers did a really great job in establishing the foundations and making it interesting and digestible.

The next step for me is to at some point see the full scenario. For example, if you have a problem in a real life and you want to build software, how do you start in your thinking process and what are the steps behind it? But I really enjoyed the two weekends, they were very interesting; maybe more so because I’m also looking forward to the next bootcamp.

 

If you could describe your experience in three words, what would you use?

  1. Positively-challenging 
  2. Enjoyable
  3. Thought-provoking

For me, that’s what made it an interesting experience, and it ticked all the boxes.

Looking to kick-start your career in Data Science or Data Analytics?

Whether you're looking to upskill to access promotions, reskill to remain relevant in your field, or transition careers, our Applied Data Analytics Bootcamp (London) can help you achieve your career objectives.

Please complete the form to the right of this text with your details and we'll get in touch and to talk through your objectives, suitability and the bootcamp.

Alternatively, click here now to book a callback with the admissions team.

Enquire now

Fill out the following form and we’ll contact you within one business day to discuss and answer any questions you have about the programme. We look forward to speaking with you.

Photo

Talk to us about our Data & Ai programmes