By Grace Abou Dib, Advanced Computing MSc student. When I was applying for my postgraduate studies at King’s College London, I had to choose between a broad programme like Advanced Computing and a specialised programme such as Artificial Intelligence, Data Science or Software Engineering that the Department of Informatics offers. As you would expect, each programme provides a defined context for your expertise in a high-demand field while also having a clear label that employers immediately understand. So why did I opt for the former option, the generalist one, that lets you study a bit of everything? The answer may not be as appealing as expected, but we’re living in the age of generalism, not specialisation.
What actually influenced my decision was job descriptions for roles I wanted to have in the near future, so that did not include entry-level ones. The conclusion I found fundamentally changed my mind about how to approach job hunting and postgraduate programme applications. Let me illustrate what I mean with a very straightforward example: A data scientist job posting from 2020, or any year before the surge of Generative AI, may have required statistical modeling, being proficient in Python as well as SQL. As opposed to today’s equivalent role that expects all of the mentioned above, in addition to knowledge of machine learning algorithms, natural language processing, experience with large language models and so on. As you can tell, the role hasn’t just expanded, but it has included responsibilities that used to belong to a completely separate position.
Building on my foundations
The way the tech market currently works is that software engineers are expected to know about security best practices, just like AI researchers need to know about software engineering. Similarly, security engineers should be familiar with AI systems and DevOps engineers must know about data science tools. There are many overlaps and they are exponentially growing. It is worth noting that this is not about companies expecting impossible standards from their employees, but rather about the nature of real-life tech problems that cannot neatly fit into academic discipline boundaries. Building a recommender system requires knowledge of machine learning, software engineering as well as system design for scalability purposes, data privacy and user experience thinking. It would be extremely hard to find a person who is specialised in all of these skills, however someone who’s equipped with a broad foundation across numerous areas can navigate such problems.
Therefore, my biggest concern with a programme like AI or Data Science is that it can give me the deep knowledge, but in that case from where would I get the broad knowledge? Advanced Computing offered me a great path to build foundations through coursework while also being able to develop deep knowledge through part-time work experience, personal projects and initiatives. What also further proves my point is that the programme is extremely diverse with students coming from various backgrounds and experiences. Some have applied straight after undergraduate studies, like I did, while others have been working in the industry for years. What interests me even more is that both groups see the value in having a foundation but for different reasons. Students with industry experience know that role boundaries are dissolving and they need to be able to work on projects and collaborate with different teams. Students coming straight from studies benefit from having a broad foundation because they have not yet discovered what they want to focus on.
Advanced Computing lets you experiment and even pivot.
A specialised programme can lock you into a path before you have fully explored the landscape, especially if you’re applying for postgraduate programmes without having worked in the industry first. Advanced Computing lets you experiment and even pivot. The diversity of backgrounds also enriches the learning environment, with group projects and classroom discussions benefiting from perspectives. My module choices reflect what I just stated in this blog: I am mostly taking AI-related courses because that is where I want to have deep knowledge; I also took “unrelated” courses like Security Engineering, Software Engineering for Financial Systems as well as Big Data Technologies. The way I thought of it is that these courses expand my skillset into areas that complement my AI work: Understanding security makes me build robust AI systems, whereas software engineering makes my models more maintainable. As per big data knowledge that helps me scale solutions beyond the prototype stage.
You can shape your education
In my opinion, this is the true power of a great programme: you can customise it to create your own unique combination of skills. You can shape your education based on where you see the field heading and where you want to position yourself. Some people might argue that a generalist programme will make you a “jack of all trades master of none”, but there’s something very crucial that needs to be taken into account: employers care more about what you can do than what your degree title is. When I am interviewing for AI roles they do not penalise me for not having “Artificial Intelligence” in my degree title, they only evaluate my AI projects, my understanding of the field, my ability to learn fast, solve their problems and think critically. And this is another added value of the generalist foundation which gives you enough adaptability so you can learn new domains quickly. It also gives you the ability to communicate with specialists in domains so you can work effectively with them. It gives you the ability to solve problems that happen at the intersection of fields. Last but not least, it gives you career flexibility so you can change your direction if your interests evolve over time.
If you are considering Advanced Computing or a similar generalist programme here is how to make it work strategically. Choose modules strategically thinking about how different areas complement each other and support your career direction. Make sure to build a portfolio that demonstrates both horizontal and vertical knowledge. Your portfolio should showcase your expertise in your core area while highlighting that you can work across domains. It is worth mentioning that choosing between a specialist and generalist programme is not about one being better than the other, but rather about which one provides you with more opportunities in the long run, while also aligning with your personal goals and vision.
King’s Advanced Computing gave me the flexibility to design my unique combination of skills: the breadth to understand how different technologies connect and the foundation to keep learning whatever becomes necessary. In a field changing as rapidly as technology, that adaptability might be the most valuable skill of all.
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