Muzz Adams

Data science spans across and is able to be utilised in so many industries. It may seem like the way of the future, but it’s already very much part of the present. As head of performance at an asset management company, I need to know what all the techy people are up to. We have a lot of quantitative people doing highly technical stuff and I needed to learn the language. I’m not going to be a coder: I did this programme because I wanted high-level concepts and industry examples of how data science works on the ground. Prior to the programme, some of my team would talk to me about asymmetric classifications or supervised artificial intelligence (AI), and I wouldn’t have a clue what they were going on about. Now I know.

The prestige of a world-leading university

I wasn’t going to pick any institution. One of the main attractions for me was LSE and its prestige. The programme was therefore a double win: number one was LSE, number two was the programme itself – which I felt was made for me – but the institution sets you apart. On the programme, it feels like a semester’s work is covered in five days, but the facilitators and lecturers adjusted their delivery according to the knowledge of the group. The high level of aptitude within the class allowed the programme to proceed at the right pace for everyone.

Six months on from the programme, it’s already had a big impact on my work. I’m speaking the language of a quantitative analyst and I can’t put a price on the confidence that’s given me in my conversations. On the programme we went into detail on concepts within the AI environment. I did the hard work and now I can fully enter into discussions at work about the new paths we’re taking with AI. I also now have a good overview of machine learning and big data and the concepts around it, which includes extracting data, interpreting the outputs and evaluating the evidence. That for me was the steepest learning curve.

A new horizon

The programme has opened my mind in many ways. Text analysis is a totally new thing for me. For example, one day we looked at Trump’s tweets using sentiment analysis as he was running for the primaries. It’s not something I would have ever been exposed to otherwise. Professor Kenneth Benoit, Professor Sabine Benoit, and the guest lecturer Pablo Barbera focus a lot on text analysis. Pablo has experience working in the technology sector so he gave a lot of practical examples and it was interesting to hear his take on data and how it works in practice.

The guy who I was sitting next to for most of my time on the Data Science for Executives programme is running to be president of Nigeria. Another person was a director of Boots, the pharmacy company, and another guy – from Korea, but based in Sweden – was running an app out of Germany. There were people from the oil industry, from the police, and from international universities. That’s the calibre and the diversity of the people who attended this programme.