Motivation shared by the motivated

We all – big tech, the academic community, universities, and the government – are faced with the task of ensuring the country’s technological development. This isn’t a task for the major companies alone – they would need trained specialists ready to create IT and AI technologies at all levels, from fundamental to managerial. It all starts with the motivation to learn – and the responsibility lies with all of us.

If we are talking about school students, then it comes down to forming a large funnel to attract younger kids to the world of computer science, AI, and robotics. In this case, we are competing for their attention with Twitch, Roblox, and other hyperpopular platforms. That’s why we have to offer education that will be able to turn their attention towards computer science and AI. This is an endeavor for big tech: for instance, Yandex invites students into its actual projects, showing the inside of the apps they use on a daily basis. This first point of contact is important; next, we need to maintain their motivation, which is much harder. Yes, unfortunately, at some schools all students do is code in Pascal. However, ITMO, Yandex, and other companies and universities offer lots of free courses for school students. Here, too, it’s a question of motivation.

Real-life examples and cases when working with students are now becoming a given. Without them, universities and companies will be working separately. This doesn’t mean that by providing students with cases, Yandex, for instance, is training their future employees – no, it’s a part of the common contribution to the country’s education system. As a result of these inputs, everyone wins out. Some universities are also ready to contribute. For example, at ITMO, we involve students in the industry’s real-world tasks and objectives in order to equip them with all the necessary tools for the competitive job market, without the need for any additional retraining. At the same time, in our graduates IT companies gain qualified specialists ready to start working from the get-go. 

Growing from the foundation

The current shortage in the AI job market is qualitative – not quantitative. There are many juniors, but not enough specialists at the middle and senior levels. While there are enough courses to prepare for junior positions, advancing further up the career ladder will be very challenging due to a lack of a “foundation.” This is one of the reasons why leading big tech companies and universities are now joining forces to train professionals with strong fundamental knowledge. Moreover, mutual support is aimed at developing future technologies – one example here is the new program by ITMO, Yandex, Sberbank, and leading Russian universities called AI360: ML Native. The program is meant to train fundamental mathematicians who will be able to create a professional community of AI “drivers.” This doesn’t mean that online courses are useless – on the contrary, they are a perfect fit for someone wishing to pick up some new skills and expand their competencies. However, fundamental training is needed to advance in IT.

Adjusting the format according to the needs

Debates continue about which format is better – online or offline? The pandemic has changed education once and for all, with the hybrid learning format now here to stay, and we have adapted to it. It is essential to focus primarily on the needs of the audience of our educational product. Each category of learners and each course have their own best-suitable format. I advocate for a combination of the two, as we cannot measure everything with the same yardstick. The trend towards online communication is still strong. In the age of fragmented thinking, the value of in-person education, when we can look each other in the eye, will increase. However, as online solutions become more prevalent, the demand for face-to-face interaction will also grow.